Example Portfolio Report

Dataset statistics

Number of variables	69
Number of observations	4964
Missing cells	388
Missing cells (%)	0.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	2.6 MiB
Average record size in memory	552.0 B

Variable types

Numeric	19
Categorical	39
Boolean	11

Warnings

`EEA_PolicyYear` has constant value "2006"	Constant
`Policy_Zip_Code_Garaging_Location` has a high cardinality: 699 distinct values	High cardinality
`Vehicle_Make_Description` has a high cardinality: 1166 distinct values	High cardinality
`PolicyNo` is highly correlated with `EEA_Policy_Tenure`	High correlation
`Vehicle_Make_Year` is highly correlated with `Vehicle_Age_In_Years` and 2 other fields	High correlation
`Vehicle_Age_In_Years` is highly correlated with `Vehicle_Make_Year` and 2 other fields	High correlation
`Vehicle_Collision_Coverage_Deductible` is highly correlated with `Vehicle_Make_Year` and 2 other fields	High correlation
`Driver_Total` is highly correlated with `Driver_Total_Married` and 1 other fields	High correlation
`Driver_Total_Male` is highly correlated with `Driver_Total_Female`	High correlation
`Driver_Total_Female` is highly correlated with `Driver_Total_Male`	High correlation
`Driver_Total_Single` is highly correlated with `Driver_Total_Married`	High correlation
`Driver_Total_Married` is highly correlated with `Driver_Total` and 3 other fields	High correlation
`Driver_Total_Related_To_Insured_Self` is highly correlated with `Driver_Total_Related_To_Insured_Spouse`	High correlation
`Driver_Total_Related_To_Insured_Spouse` is highly correlated with `Driver_Total_Married` and 1 other fields	High correlation
`Driver_Total_Related_To_Insured_Child` is highly correlated with `Driver_Total_Teenager_Age_15_19`	High correlation
`Driver_Total_Licensed_In_State` is highly correlated with `Driver_Total` and 1 other fields	High correlation
`Driver_Minimum_Age` is highly correlated with `Driver_Maximum_Age` and 1 other fields	High correlation
`Driver_Maximum_Age` is highly correlated with `Driver_Minimum_Age` and 1 other fields	High correlation
`Driver_Total_Teenager_Age_15_19` is highly correlated with `Driver_Total_Related_To_Insured_Child`	High correlation
`Driver_Total_Upper_Senior_Ages_70_plus` is highly correlated with `Driver_Minimum_Age` and 1 other fields	High correlation
`EEA_Policy_Tenure` is highly correlated with `PolicyNo`	High correlation
`Annual_Premium` is highly correlated with `Vehicle_Make_Year` and 2 other fields	High correlation
`Loss_Amount` is highly correlated with `Severity` and 1 other fields	High correlation
`Severity` is highly correlated with `Loss_Amount` and 1 other fields	High correlation
`Loss_Ratio` is highly correlated with `Loss_Amount` and 1 other fields	High correlation
`PolicyNo` is highly correlated with `EEA_Policy_Tenure`	High correlation
`Vehicle_Make_Year` is highly correlated with `Vehicle_Symbol` and 3 other fields	High correlation
`Vehicle_Symbol` is highly correlated with `Vehicle_Make_Year` and 1 other fields	High correlation
`Vehicle_Age_In_Years` is highly correlated with `Vehicle_Make_Year` and 2 other fields	High correlation
`Vehicle_Collision_Coverage_Deductible` is highly correlated with `Vehicle_Make_Year` and 2 other fields	High correlation
`Driver_Total` is highly correlated with `Driver_Total_Licensed_In_State`	High correlation
`Driver_Total_Male` is highly correlated with `Driver_Total_Female`	High correlation
`Driver_Total_Female` is highly correlated with `Driver_Total_Male`	High correlation
`Driver_Total_Single` is highly correlated with `Driver_Total_Married`	High correlation
`Driver_Total_Married` is highly correlated with `Driver_Total_Single` and 1 other fields	High correlation
`Driver_Total_Related_To_Insured_Self` is highly correlated with `Driver_Total_Related_To_Insured_Spouse`	High correlation
`Driver_Total_Related_To_Insured_Spouse` is highly correlated with `Driver_Total_Married` and 1 other fields	High correlation
`Driver_Total_Related_To_Insured_Child` is highly correlated with `Driver_Total_Teenager_Age_15_19`	High correlation
`Driver_Total_Licensed_In_State` is highly correlated with `Driver_Total`	High correlation
`Driver_Minimum_Age` is highly correlated with `Driver_Maximum_Age`	High correlation
`Driver_Maximum_Age` is highly correlated with `Driver_Minimum_Age`	High correlation
`Driver_Total_Teenager_Age_15_19` is highly correlated with `Driver_Total_Related_To_Insured_Child`	High correlation
`EEA_Policy_Tenure` is highly correlated with `PolicyNo`	High correlation
`Annual_Premium` is highly correlated with `Vehicle_Make_Year` and 3 other fields	High correlation
`Claim_Count` is highly correlated with `Loss_Amount` and 3 other fields	High correlation
`Loss_Amount` is highly correlated with `Claim_Count` and 3 other fields	High correlation
`Frequency` is highly correlated with `Claim_Count` and 3 other fields	High correlation
`Severity` is highly correlated with `Claim_Count` and 3 other fields	High correlation
`Loss_Ratio` is highly correlated with `Claim_Count` and 3 other fields	High correlation
`PolicyNo` is highly correlated with `EEA_Policy_Tenure`	High correlation
`Vehicle_Make_Year` is highly correlated with `Vehicle_Age_In_Years` and 2 other fields	High correlation
`Vehicle_Age_In_Years` is highly correlated with `Vehicle_Make_Year` and 1 other fields	High correlation
`Vehicle_Collision_Coverage_Deductible` is highly correlated with `Vehicle_Make_Year` and 2 other fields	High correlation
`Driver_Total` is highly correlated with `Driver_Total_Licensed_In_State`	High correlation
`Driver_Total_Male` is highly correlated with `Driver_Total_Female`	High correlation
`Driver_Total_Female` is highly correlated with `Driver_Total_Male`	High correlation
`Driver_Total_Single` is highly correlated with `Driver_Total_Married`	High correlation
`Driver_Total_Married` is highly correlated with `Driver_Total_Single` and 1 other fields	High correlation
`Driver_Total_Related_To_Insured_Self` is highly correlated with `Driver_Total_Related_To_Insured_Spouse`	High correlation
`Driver_Total_Related_To_Insured_Spouse` is highly correlated with `Driver_Total_Married` and 1 other fields	High correlation
`Driver_Total_Related_To_Insured_Child` is highly correlated with `Driver_Total_Teenager_Age_15_19`	High correlation
`Driver_Total_Licensed_In_State` is highly correlated with `Driver_Total`	High correlation
`Driver_Minimum_Age` is highly correlated with `Driver_Maximum_Age`	High correlation
`Driver_Maximum_Age` is highly correlated with `Driver_Minimum_Age`	High correlation
`Driver_Total_Teenager_Age_15_19` is highly correlated with `Driver_Total_Related_To_Insured_Child`	High correlation
`EEA_Policy_Tenure` is highly correlated with `PolicyNo`	High correlation
`Annual_Premium` is highly correlated with `Vehicle_Make_Year` and 1 other fields	High correlation
`Claim_Count` is highly correlated with `Loss_Amount` and 3 other fields	High correlation
`Loss_Amount` is highly correlated with `Claim_Count` and 3 other fields	High correlation
`Frequency` is highly correlated with `Claim_Count` and 3 other fields	High correlation
`Severity` is highly correlated with `Claim_Count` and 3 other fields	High correlation
`Loss_Ratio` is highly correlated with `Claim_Count` and 3 other fields	High correlation
`Vehicle_Collision_Coverage_Indicator` is highly correlated with `EEA_Packaged_Policy_Indicator` and 8 other fields	High correlation
`Driver_Total_College_Ages_20_23` is highly correlated with `Driver_Minimum_Age` and 2 other fields	High correlation
`EEA_Packaged_Policy_Indicator` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 4 other fields	High correlation
`EEA_Agency_Type` is highly correlated with `EEA_Policy_Zip_Code_3`	High correlation
`Vehicle_Symbol` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 3 other fields	High correlation
`Driver_Minimum_Age` is highly correlated with `Driver_Total_College_Ages_20_23` and 13 other fields	High correlation
`Vehicle_Passive_Restraint` is highly correlated with `Vehicle_Make_Year` and 1 other fields	High correlation
`Driver_Total_Related_To_Insured_Spouse` is highly correlated with `Driver_Total_Married` and 4 other fields	High correlation
`Driver_Total_Upper_Senior_Ages_70_plus` is highly correlated with `Driver_Minimum_Age` and 1 other fields	High correlation
`Loss_Amount` is highly correlated with `Loss_Ratio` and 1 other fields	High correlation
`Driver_Total_Licensed_In_State` is highly correlated with `Driver_Total_Married` and 1 other fields	High correlation
`Driver_Total_Senior_Ages_65_69` is highly correlated with `Driver_Minimum_Age` and 1 other fields	High correlation
`Vehicle_Bodily_Injury_Limit` is highly correlated with `Vehicle_Physical_Damage_Limit` and 1 other fields	High correlation
`Vehicle_Youthful_Driver_Training_Code` is highly correlated with `Driver_Minimum_Age` and 5 other fields	High correlation
`Loss_Ratio` is highly correlated with `Loss_Amount` and 2 other fields	High correlation
`EEA_Full_Coverage_Indicator` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 8 other fields	High correlation
`Vehicle_Physical_Damage_Limit` is highly correlated with `Vehicle_Bodily_Injury_Limit` and 1 other fields	High correlation
`Vehicle_Anti_Theft_Device` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 4 other fields	High correlation
`Driver_Total_Adult_Ages_50_64` is highly correlated with `Driver_Minimum_Age` and 5 other fields	High correlation
`Severity` is highly correlated with `Loss_Amount` and 1 other fields	High correlation
`EEA_Policy_Tenure` is highly correlated with `PolicyNo` and 1 other fields	High correlation
`Driver_Total_Married` is highly correlated with `Driver_Total_Related_To_Insured_Spouse` and 8 other fields	High correlation
`Driver_Total_Female` is highly correlated with `Driver_Total_Related_To_Insured_Spouse` and 3 other fields	High correlation
`PolicyNo` is highly correlated with `EEA_Policy_Tenure` and 2 other fields	High correlation
`Annual_Premium` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 7 other fields	High correlation
`Driver_Total_Single` is highly correlated with `Driver_Minimum_Age` and 4 other fields	High correlation
`Vehicle_Safe_Driver_Discount_Indicator` is highly correlated with `EEA_Policy_Tenure` and 2 other fields	High correlation
`EEA_Multi_Auto_Policies_Indicator` is highly correlated with `EEA_Packaged_Policy_Indicator`	High correlation
`Policy_Billing_Code` is highly correlated with `Annual_Premium` and 1 other fields	High correlation
`Driver_Total_Young_Adult_Ages_24_29` is highly correlated with `Driver_Minimum_Age` and 1 other fields	High correlation
`Driver_Total` is highly correlated with `Driver_Total_Related_To_Insured_Spouse` and 7 other fields	High correlation
`Driver_Total_Low_Middle_Adult_Ages_30_39` is highly correlated with `Driver_Minimum_Age` and 4 other fields	High correlation
`Vehicle_Annual_Miles` is highly correlated with `Vehicle_Days_Per_Week_Driven`	High correlation
`Vehicle_Make_Year` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 5 other fields	High correlation
`Policy_Installment_Term` is highly correlated with `Annual_Premium` and 1 other fields	High correlation
`Vehicle_Days_Per_Week_Driven` is highly correlated with `Vehicle_Annual_Miles`	High correlation
`Vehicle_Miles_To_Work` is highly correlated with `Vehicle_Usage`	High correlation
`Vehicle_Youthful_Driver_Indicator` is highly correlated with `Driver_Minimum_Age` and 3 other fields	High correlation
`Vehicle_Youthful_Good_Student_Code` is highly correlated with `Vehicle_Youthful_Driver_Training_Code` and 1 other fields	High correlation
`Driver_Total_Related_To_Insured_Self` is highly correlated with `Driver_Total_Related_To_Insured_Spouse` and 2 other fields	High correlation
`Driver_Total_Related_To_Insured_Child` is highly correlated with `Driver_Total_College_Ages_20_23` and 6 other fields	High correlation
`Frequency` is highly correlated with `Loss_Ratio`	High correlation
`EEA_Policy_Zip_Code_3` is highly correlated with `EEA_Agency_Type` and 1 other fields	High correlation
`Vehicle_Territory` is highly correlated with `EEA_Policy_Zip_Code_3`	High correlation
`Driver_Total_Male` is highly correlated with `Driver_Total_Married` and 3 other fields	High correlation
`Vehicle_Usage` is highly correlated with `Vehicle_Miles_To_Work`	High correlation
`Driver_Total_Teenager_Age_15_19` is highly correlated with `Driver_Minimum_Age` and 4 other fields	High correlation
`Vehicle_Driver_Points` is highly correlated with `Vehicle_Safe_Driver_Discount_Indicator`	High correlation
`Driver_Maximum_Age` is highly correlated with `Driver_Total_College_Ages_20_23` and 12 other fields	High correlation
`EEA_Prior_Bodily_Injury_Limit` is highly correlated with `Vehicle_Bodily_Injury_Limit` and 1 other fields	High correlation
`Vehicle_Comprehensive_Coverage_Indicator` is highly correlated with `Vehicle_Comprehensive_Coverage_Limit`	High correlation
`Vehicle_Number_Of_Drivers_Assigned` is highly correlated with `Driver_Minimum_Age` and 1 other fields	High correlation
`Vehicle_Collision_Coverage_Deductible` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 2 other fields	High correlation
`Vehicle_Performance` is highly correlated with `Vehicle_Symbol`	High correlation
`SYS_New_Business` is highly correlated with `PolicyNo`	High correlation
`Vehicle_Age_In_Years` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 4 other fields	High correlation
`EEA_Liability_Coverage_Only_Indicator` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 5 other fields	High correlation
`Vehicle_Comprehensive_Coverage_Limit` is highly correlated with `Vehicle_Comprehensive_Coverage_Indicator`	High correlation
`Driver_Total_Middle_Adult_Ages_40_49` is highly correlated with `Driver_Minimum_Age` and 4 other fields	High correlation
`EEA_Multi_Auto_Policies_Indicator` is highly correlated with `EEA_PolicyYear`	High correlation
`Policy_Billing_Code` is highly correlated with `Policy_Installment_Term` and 1 other fields	High correlation
`Vehicle_Collision_Coverage_Indicator` is highly correlated with `EEA_Full_Coverage_Indicator` and 2 other fields	High correlation
`Driver_Total_College_Ages_20_23` is highly correlated with `Vehicle_Youthful_Driver_Indicator` and 1 other fields	High correlation
`Driver_Total_Young_Adult_Ages_24_29` is highly correlated with `EEA_PolicyYear`	High correlation
`Driver_Total` is highly correlated with `Driver_Total_Licensed_In_State` and 2 other fields	High correlation
`EEA_Packaged_Policy_Indicator` is highly correlated with `EEA_Liability_Coverage_Only_Indicator` and 1 other fields	High correlation
`Policy_Company` is highly correlated with `EEA_PolicyYear`	High correlation
`EEA_Agency_Type` is highly correlated with `EEA_PolicyYear`	High correlation
`Driver_Total_Low_Middle_Adult_Ages_30_39` is highly correlated with `EEA_PolicyYear`	High correlation
`Vehicle_Annual_Miles` is highly correlated with `EEA_PolicyYear`	High correlation
`Policy_Installment_Term` is highly correlated with `Policy_Billing_Code` and 1 other fields	High correlation
`Vehicle_Days_Per_Week_Driven` is highly correlated with `EEA_PolicyYear`	High correlation
`Policy_Method_Of_Payment` is highly correlated with `EEA_PolicyYear`	High correlation
`Vehicle_Youthful_Driver_Indicator` is highly correlated with `Driver_Total_College_Ages_20_23` and 5 other fields	High correlation
`Vehicle_Passive_Restraint` is highly correlated with `EEA_PolicyYear`	High correlation
`Vehicle_Youthful_Good_Student_Code` is highly correlated with `EEA_PolicyYear`	High correlation
`Driver_Total_Related_To_Insured_Self` is highly correlated with `EEA_PolicyYear`	High correlation
`Driver_Total_Related_To_Insured_Spouse` is highly correlated with `EEA_PolicyYear`	High correlation
`Driver_Total_Related_To_Insured_Child` is highly correlated with `Vehicle_Youthful_Driver_Indicator` and 3 other fields	High correlation
`Driver_Total_Upper_Senior_Ages_70_plus` is highly correlated with `EEA_PolicyYear`	High correlation
`EEA_Policy_Zip_Code_3` is highly correlated with `EEA_PolicyYear`	High correlation
`Driver_Total_Male` is highly correlated with `Driver_Total_Female` and 1 other fields	High correlation
`Driver_Total_Licensed_In_State` is highly correlated with `Driver_Total` and 2 other fields	High correlation
`Driver_Total_Senior_Ages_65_69` is highly correlated with `EEA_PolicyYear`	High correlation
`Vehicle_Usage` is highly correlated with `EEA_PolicyYear`	High correlation
`Driver_Total_Teenager_Age_15_19` is highly correlated with `Vehicle_Youthful_Driver_Indicator` and 3 other fields	High correlation
`Vehicle_Bodily_Injury_Limit` is highly correlated with `EEA_Prior_Bodily_Injury_Limit` and 2 other fields	High correlation
`Vehicle_Driver_Points` is highly correlated with `EEA_PolicyYear`	High correlation
`Vehicle_Youthful_Driver_Training_Code` is highly correlated with `Vehicle_Youthful_Driver_Indicator` and 3 other fields	High correlation
`SYS_Renewed` is highly correlated with `EEA_PolicyYear`	High correlation
`Policy_Reinstatement_Fee_Indicator` is highly correlated with `EEA_PolicyYear`	High correlation
`EEA_Prior_Bodily_Injury_Limit` is highly correlated with `Vehicle_Bodily_Injury_Limit` and 2 other fields	High correlation
`Vehicle_Comprehensive_Coverage_Indicator` is highly correlated with `Vehicle_Bodily_Injury_Limit` and 2 other fields	High correlation
`EEA_Full_Coverage_Indicator` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 2 other fields	High correlation
`Vehicle_Number_Of_Drivers_Assigned` is highly correlated with `EEA_PolicyYear`	High correlation
`Vehicle_Performance` is highly correlated with `EEA_PolicyYear`	High correlation
`SYS_New_Business` is highly correlated with `EEA_PolicyYear`	High correlation
`Vehicle_Anti_Theft_Device` is highly correlated with `EEA_PolicyYear`	High correlation
`Driver_Total_Adult_Ages_50_64` is highly correlated with `EEA_PolicyYear`	High correlation
`Driver_Total_Married` is highly correlated with `Driver_Total` and 2 other fields	High correlation
`Driver_Total_Female` is highly correlated with `Driver_Total_Male` and 1 other fields	High correlation
`Claim_Count` is highly correlated with `EEA_PolicyYear`	High correlation
`EEA_Liability_Coverage_Only_Indicator` is highly correlated with `Vehicle_Collision_Coverage_Indicator` and 3 other fields	High correlation
`Driver_Total_Single` is highly correlated with `Vehicle_Youthful_Driver_Indicator` and 1 other fields	High correlation
`EEA_PolicyYear` is highly correlated with `EEA_Multi_Auto_Policies_Indicator` and 46 other fields	High correlation
`Driver_Total_Middle_Adult_Ages_40_49` is highly correlated with `EEA_PolicyYear`	High correlation
`Vehicle_Safe_Driver_Discount_Indicator` is highly correlated with `EEA_PolicyYear`	High correlation
`Vehicle_Bodily_Injury_Limit` has 194 (3.9%) missing values	Missing
`EEA_Prior_Bodily_Injury_Limit` has 194 (3.9%) missing values	Missing
`Loss_Amount` is highly skewed (γ1 = 51.00506603)	Skewed
`Frequency` is highly skewed (γ1 = 46.5164757)	Skewed
`Severity` is highly skewed (γ1 = 51.69328358)	Skewed
`Loss_Ratio` is highly skewed (γ1 = 40.7590306)	Skewed
`PolicyNo` has unique values	Unique
`EEA_Policy_Tenure` has 459 (9.2%) zeros	Zeros
`Loss_Amount` has 4715 (95.0%) zeros	Zeros
`Frequency` has 4715 (95.0%) zeros	Zeros
`Severity` has 4715 (95.0%) zeros	Zeros
`Loss_Ratio` has 4715 (95.0%) zeros	Zeros

Reproduction

Analysis started	2021-09-12 18:15:37.129951
Analysis finished	2021-09-12 18:16:15.959715
Duration	38.83 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

PolicyNo
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	4964
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	315892133.9

Minimum	164562033
Maximum	381258900
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	164562033
5-th percentile	193920276
Q1	286336490.2
median	334182807.5
Q3	361190102.8
95-th percentile	376035380.9
Maximum	381258900
Range	216696867
Interquartile range (IQR)	74853612.5

Descriptive statistics

Standard deviation	56810824.85
Coefficient of variation (CV)	0.1798424803
Kurtosis	-0.01405011463
Mean	315892133.9
Median Absolute Deviation (MAD)	31945944
Skewness	-1.008111599
Sum	1.568088553 × 10¹²
Variance	3.22746982 × 10¹⁵
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
352275105	1	< 0.1%
353686203	1	< 0.1%
352624803	1	< 0.1%
336214706	1	< 0.1%
333091507	1	< 0.1%
363256502	1	< 0.1%
246944439	1	< 0.1%
289516216	1	< 0.1%
376888200	1	< 0.1%
353839804	1	< 0.1%
Other values (4954)	4954	99.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
164562033	1	< 0.1%
165119133	1	< 0.1%
165166239	1	< 0.1%
165198832	1	< 0.1%
165319534	1	< 0.1%
165355034	1	< 0.1%
165386232	1	< 0.1%
165708632	1	< 0.1%
165951132	1	< 0.1%
165971032	1	< 0.1%

Value	Count	Frequency (%)
381258900	1	< 0.1%
381184700	1	< 0.1%
381148600	1	< 0.1%
381140200	1	< 0.1%
381137600	1	< 0.1%
381080800	1	< 0.1%
381052900	1	< 0.1%
381040600	1	< 0.1%
381039600	1	< 0.1%
381020700	1	< 0.1%

Policy_Company
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Standard	4679
Preferred	285

Length

Max length	9
Median length	9
Mean length	9
Min length	9

Characters and Unicode

Total characters	44676
Distinct characters	10
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Standard
2nd row	Standard
3rd row	Standard
4th row	Standard
5th row	Standard

Common Values

Value	Count	Frequency (%)
Standard	4679	94.3%
Preferred	285	5.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
standard	4679	94.3%
preferred	285	5.7%

Most occurring characters

Value	Count	Frequency (%)
d	9643	21.6%
a	9358	20.9%
r	5534	12.4%
S	4679	10.5%
t	4679	10.5%
n	4679	10.5%
	4679	10.5%
e	855	1.9%
P	285	0.6%
f	285	0.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	35033	78.4%
Uppercase Letter	4964	11.1%
Space Separator	4679	10.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
d	9643	27.5%
a	9358	26.7%
r	5534	15.8%
t	4679	13.4%
n	4679	13.4%
e	855	2.4%
f	285	0.8%

Uppercase Letter

Value	Count	Frequency (%)
S	4679	94.3%
P	285	5.7%

Space Separator

Value	Count	Frequency (%)
	4679	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	39997	89.5%
Common	4679	10.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
d	9643	24.1%
a	9358	23.4%
r	5534	13.8%
S	4679	11.7%
t	4679	11.7%
n	4679	11.7%
e	855	2.1%
P	285	0.7%
f	285	0.7%

Common

Value	Count	Frequency (%)
	4679	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	44676	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
d	9643	21.6%
a	9358	20.9%
r	5534	12.4%
S	4679	10.5%
t	4679	10.5%
n	4679	10.5%
	4679	10.5%
e	855	1.9%
P	285	0.6%
f	285	0.6%

Policy_Installment_Term
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

6	4781
12	183

Length

Max length	2
Median length	1
Mean length	1.036865431
Min length	1

Characters and Unicode

Total characters	5147
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	6
2nd row	6
3rd row	6
4th row	6
5th row	6

Common Values

Value	Count	Frequency (%)
6	4781	96.3%
12	183	3.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
6	4781	96.3%
12	183	3.7%

Most occurring characters

Value	Count	Frequency (%)
6	4781	92.9%
1	183	3.6%
2	183	3.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	5147	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
6	4781	92.9%
1	183	3.6%
2	183	3.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	5147	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
6	4781	92.9%
1	183	3.6%
2	183	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5147	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
6	4781	92.9%
1	183	3.6%
2	183	3.6%

Policy_Billing_Code
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Direct Billed to Insured	4863
Premium Finance	101

Length

Max length	24
Median length	24
Mean length	23.81688155
Min length	15

Characters and Unicode

Total characters	118227
Distinct characters	19
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Direct Billed to Insured
2nd row	Direct Billed to Insured
3rd row	Direct Billed to Insured
4th row	Direct Billed to Insured
5th row	Direct Billed to Insured

Common Values

Value	Count	Frequency (%)
Direct Billed to Insured	4863	98.0%
Premium Finance	101	2.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
to	4863	24.7%
insured	4863	24.7%
direct	4863	24.7%
billed	4863	24.7%
premium	101	0.5%
finance	101	0.5%

Most occurring characters

Value	Count	Frequency (%)
e	14791	12.5%
	14690	12.4%
i	9928	8.4%
r	9827	8.3%
t	9726	8.2%
l	9726	8.2%
d	9726	8.2%
n	5065	4.3%
c	4964	4.2%
u	4964	4.2%
Other values (9)	24820	21.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	88746	75.1%
Uppercase Letter	14791	12.5%
Space Separator	14690	12.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	14791	16.7%
i	9928	11.2%
r	9827	11.1%
t	9726	11.0%
l	9726	11.0%
d	9726	11.0%
n	5065	5.7%
c	4964	5.6%
u	4964	5.6%
o	4863	5.5%
Other values (3)	5166	5.8%

Uppercase Letter

Value	Count	Frequency (%)
D	4863	32.9%
B	4863	32.9%
I	4863	32.9%
P	101	0.7%
F	101	0.7%

Space Separator

Value	Count	Frequency (%)
	14690	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	103537	87.6%
Common	14690	12.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	14791	14.3%
i	9928	9.6%
r	9827	9.5%
t	9726	9.4%
l	9726	9.4%
d	9726	9.4%
n	5065	4.9%
c	4964	4.8%
u	4964	4.8%
D	4863	4.7%
Other values (8)	19957	19.3%

Common

Value	Count	Frequency (%)
	14690	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	118227	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	14791	12.5%
	14690	12.4%
i	9928	8.4%
r	9827	8.3%
t	9726	8.2%
l	9726	8.2%
d	9726	8.2%
n	5065	4.3%
c	4964	4.2%
u	4964	4.2%
Other values (9)	24820	21.0%

Policy_Method_Of_Payment
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Installment	2572
Pre-paid	2392

Length

Max length	11
Median length	11
Mean length	9.55439162
Min length	8

Characters and Unicode

Total characters	47428
Distinct characters	14
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Pre-paid
2nd row	Pre-paid
3rd row	Pre-paid
4th row	Installment
5th row	Pre-paid

Common Values

Value	Count	Frequency (%)
Installment	2572	51.8%
Pre-paid	2392	48.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
installment	2572	51.8%
pre-paid	2392	48.2%

Most occurring characters

Value	Count	Frequency (%)
n	5144	10.8%
t	5144	10.8%
l	5144	10.8%
e	4964	10.5%
a	4964	10.5%
I	2572	5.4%
s	2572	5.4%
m	2572	5.4%
P	2392	5.0%
r	2392	5.0%
Other values (4)	9568	20.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	40072	84.5%
Uppercase Letter	4964	10.5%
Dash Punctuation	2392	5.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	5144	12.8%
t	5144	12.8%
l	5144	12.8%
e	4964	12.4%
a	4964	12.4%
s	2572	6.4%
m	2572	6.4%
r	2392	6.0%
p	2392	6.0%
i	2392	6.0%

Uppercase Letter

Value	Count	Frequency (%)
I	2572	51.8%
P	2392	48.2%

Dash Punctuation

Value	Count	Frequency (%)
-	2392	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	45036	95.0%
Common	2392	5.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	5144	11.4%
t	5144	11.4%
l	5144	11.4%
e	4964	11.0%
a	4964	11.0%
I	2572	5.7%
s	2572	5.7%
m	2572	5.7%
P	2392	5.3%
r	2392	5.3%
Other values (3)	7176	15.9%

Common

Value	Count	Frequency (%)
-	2392	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	47428	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	5144	10.8%
t	5144	10.8%
l	5144	10.8%
e	4964	10.5%
a	4964	10.5%
I	2572	5.4%
s	2572	5.4%
m	2572	5.4%
P	2392	5.0%
r	2392	5.0%
Other values (4)	9568	20.2%

Policy_Reinstatement_Fee_Indicator
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

False	4385
True	579

Common Values
Chart

Value	Count	Frequency (%)
False	4385	88.3%
True	579	11.7%

Policy_Zip_Code_Garaging_Location
Categorical

HIGH CARDINALITY

Distinct	699
Distinct (%)	14.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

43025	52
43050	48
42922	43
42878	43
43046	42
Other values (694)	4736

Length

Max length	7
Median length	5
Mean length	5.010878324
Min length	5

Characters and Unicode

Total characters	24874
Distinct characters	15
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	127 ?
Unique (%)	2.6%

Sample

1st row	42602
2nd row	42857
3rd row	42980
4th row	43050
5th row	42496

Common Values

Value	Count	Frequency (%)
43025	52	1.0%
43050	48	1.0%
42922	43	0.9%
42878	43	0.9%
43046	42	0.8%
42873	40	0.8%
43066	38	0.8%
42988	37	0.7%
42462	34	0.7%
43169	33	0.7%
Other values (689)	4554	91.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
43025	52	1.0%
43050	48	1.0%
42878	43	0.9%
42922	43	0.9%
43046	42	0.8%
42873	40	0.8%
43066	38	0.8%
42988	37	0.7%
42462	34	0.7%
43169	33	0.7%
Other values (689)	4554	91.7%

Most occurring characters

Value	Count	Frequency (%)
4	6605	26.6%
2	3537	14.2%
3	3067	12.3%
8	2189	8.8%
5	1768	7.1%
0	1645	6.6%
6	1630	6.6%
9	1574	6.3%
7	1420	5.7%
1	1250	5.0%
Other values (5)	189	0.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	24685	99.2%
Lowercase Letter	162	0.7%
Uppercase Letter	27	0.1%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
4	6605	26.8%
2	3537	14.3%
3	3067	12.4%
8	2189	8.9%
5	1768	7.2%
0	1645	6.7%
6	1630	6.6%
9	1574	6.4%
7	1420	5.8%
1	1250	5.1%

Lowercase Letter

Value	Count	Frequency (%)
n	81	50.0%
k	27	16.7%
o	27	16.7%
w	27	16.7%

Uppercase Letter

Value	Count	Frequency (%)
U	27	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	24685	99.2%
Latin	189	0.8%

Most frequent character per script

Common

Value	Count	Frequency (%)
4	6605	26.8%
2	3537	14.3%
3	3067	12.4%
8	2189	8.9%
5	1768	7.2%
0	1645	6.7%
6	1630	6.6%
9	1574	6.4%
7	1420	5.8%
1	1250	5.1%

Latin

Value	Count	Frequency (%)
n	81	42.9%
U	27	14.3%
k	27	14.3%
o	27	14.3%
w	27	14.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24874	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
4	6605	26.6%
2	3537	14.2%
3	3067	12.3%
8	2189	8.8%
5	1768	7.1%
0	1645	6.6%
6	1630	6.6%
9	1574	6.3%
7	1420	5.7%
1	1250	5.0%
Other values (5)	189	0.8%

Vehicle_Territory
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	16
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	31.10374698

Minimum	13
Maximum	37
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	13
5-th percentile	20
Q1	30
median	31
Q3	35
95-th percentile	35
Maximum	37
Range	24
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	4.17778323
Coefficient of variation (CV)	0.1343176831
Kurtosis	6.114006456
Mean	31.10374698
Median Absolute Deviation (MAD)	1
Skewness	-2.129050807
Sum	154399
Variance	17.45387272
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=16)

Value	Count	Frequency (%)
31	2096	42.2%
35	1304	26.3%
30	775	15.6%
27	197	4.0%
32	120	2.4%
37	105	2.1%
17	62	1.2%
26	54	1.1%
13	54	1.1%
20	44	0.9%
Other values (6)	153	3.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
13	54	1.1%
15	21	0.4%
16	34	0.7%
17	62	1.2%
18	14	0.3%
19	28	0.6%
20	44	0.9%
22	15	0.3%
26	54	1.1%
27	197	4.0%

Value	Count	Frequency (%)
37	105	2.1%
36	41	0.8%
35	1304	26.3%
32	120	2.4%
31	2096	42.2%
30	775	15.6%
27	197	4.0%
26	54	1.1%
22	15	0.3%
20	44	0.9%

Vehicle_Make_Year
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	50
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1996.703666

Minimum	1939
Maximum	2007
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	1939
5-th percentile	1984
Q1	1993
median	1998
Q3	2002
95-th percentile	2005
Maximum	2007
Range	68
Interquartile range (IQR)	9

Descriptive statistics

Standard deviation	7.402684426
Coefficient of variation (CV)	0.003707452713
Kurtosis	4.022597618
Mean	1996.703666
Median Absolute Deviation (MAD)	4
Skewness	-1.559335897
Sum	9911637
Variance	54.79973671
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2000	356	7.2%
1999	314	6.3%
2002	307	6.2%
2001	305	6.1%
1997	298	6.0%
1998	297	6.0%
2004	296	6.0%
2005	281	5.7%
2003	267	5.4%
1995	253	5.1%
Other values (40)	1990	40.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1939	1	< 0.1%
1955	2	< 0.1%
1956	1	< 0.1%
1957	2	< 0.1%
1958	1	< 0.1%
1963	3	0.1%
1964	5	0.1%
1965	3	0.1%
1966	12	0.2%
1967	3	0.1%

Value	Count	Frequency (%)
2007	44	0.9%
2006	193	3.9%
2005	281	5.7%
2004	296	6.0%
2003	267	5.4%
2002	307	6.2%
2001	305	6.1%
2000	356	7.2%
1999	314	6.3%
1998	297	6.0%

Vehicle_Make_Description
Categorical

HIGH CARDINALITY

Distinct	1166
Distinct (%)	23.5%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

FORD F150	165
CHEV PICKUP1500	130
FORD RANGER	120
CHEV S10 PICKUP	105
CHEV SILVER1500	91
Other values (1161)	4353

Length

Max length	18
Median length	17
Mean length	16.99979855
Min length	16

Characters and Unicode

Total characters	84387
Distinct characters	43
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	574 ?
Unique (%)	11.6%

Sample

1st row	DODG CARAVAN SE
2nd row	BUIK REG LS-LSE
3rd row	FORD TRUCK
4th row	TYTA TUNDRA SR5
5th row	CHEV CAMARO RS

Common Values

Value	Count	Frequency (%)
FORD F150	165	3.3%
CHEV PICKUP1500	130	2.6%
FORD RANGER	120	2.4%
CHEV S10 PICKUP	105	2.1%
CHEV SILVER1500	91	1.8%
TYTA CAMRY	78	1.6%
HOND ACCORD EX	75	1.5%
DODG RAM PU1500	75	1.5%
FORD EXPLORER	71	1.4%
HOND ACCORD LX	63	1.3%
Other values (1156)	3991	80.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ford	1171	9.5%
chev	1044	8.4%
tyta	366	3.0%
dodg	317	2.6%
hond	266	2.2%
f150	235	1.9%
pickup	215	1.7%
nssn	210	1.7%
jeep	196	1.6%
gmc	190	1.5%
Other values (1042)	8153	65.9%

Most occurring characters

Value	Count	Frequency (%)
	26120	31.0%
R	5044	6.0%
E	4577	5.4%
C	3725	4.4%
A	3692	4.4%
O	3465	4.1%
D	3240	3.8%
S	3189	3.8%
T	2765	3.3%
L	2595	3.1%
Other values (33)	25975	30.8%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	53159	63.0%
Space Separator	26120	31.0%
Decimal Number	4456	5.3%
Dash Punctuation	597	0.7%
Other Punctuation	53	0.1%
Open Punctuation	1	< 0.1%
Math Symbol	1	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
R	5044	9.5%
E	4577	8.6%
C	3725	7.0%
A	3692	6.9%
O	3465	6.5%
D	3240	6.1%
S	3189	6.0%
T	2765	5.2%
L	2595	4.9%
N	2373	4.5%
Other values (16)	18494	34.8%

Decimal Number

Value	Count	Frequency (%)
0	1840	41.3%
1	997	22.4%
5	975	21.9%
2	264	5.9%
3	147	3.3%
4	100	2.2%
8	59	1.3%
6	28	0.6%
7	25	0.6%
9	21	0.5%

Other Punctuation

Value	Count	Frequency (%)
.	33	62.3%
&	16	30.2%
\	4	7.5%

Space Separator

Value	Count	Frequency (%)
	26120	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	597	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	1	100.0%

Math Symbol

Value	Count	Frequency (%)
+	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	53159	63.0%
Common	31228	37.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
R	5044	9.5%
E	4577	8.6%
C	3725	7.0%
A	3692	6.9%
O	3465	6.5%
D	3240	6.1%
S	3189	6.0%
T	2765	5.2%
L	2595	4.9%
N	2373	4.5%
Other values (16)	18494	34.8%

Common

Value	Count	Frequency (%)
	26120	83.6%
0	1840	5.9%
1	997	3.2%
5	975	3.1%
-	597	1.9%
2	264	0.8%
3	147	0.5%
4	100	0.3%
8	59	0.2%
.	33	0.1%
Other values (7)	96	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	84387	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	26120	31.0%
R	5044	6.0%
E	4577	5.4%
C	3725	4.4%
A	3692	4.4%
O	3465	4.1%
D	3240	3.8%
S	3189	3.8%
T	2765	3.3%
L	2595	3.1%
Other values (33)	25975	30.8%

Vehicle_Performance
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Standard	4725
Intermediate	134
High	72
Sports Premium	22
Sports	11

Length

Max length	14
Median length	8
Mean length	8.072119259
Min length	4

Characters and Unicode

Total characters	40070
Distinct characters	19
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Standard
2nd row	Standard
3rd row	Standard
4th row	Standard
5th row	Sports

Common Values

Value	Count	Frequency (%)
Standard	4725	95.2%
Intermediate	134	2.7%
High	72	1.5%
Sports Premium	22	0.4%
Sports	11	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
standard	4725	94.8%
intermediate	134	2.7%
high	72	1.4%
sports	33	0.7%
premium	22	0.4%

Most occurring characters

Value	Count	Frequency (%)
a	9584	23.9%
d	9584	23.9%
t	5026	12.5%
r	4914	12.3%
n	4859	12.1%
S	4758	11.9%
e	424	1.1%
i	228	0.6%
m	178	0.4%
I	134	0.3%
Other values (9)	381	1.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	35062	87.5%
Uppercase Letter	4986	12.4%
Space Separator	22	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	9584	27.3%
d	9584	27.3%
t	5026	14.3%
r	4914	14.0%
n	4859	13.9%
e	424	1.2%
i	228	0.7%
m	178	0.5%
g	72	0.2%
h	72	0.2%
Other values (4)	121	0.3%

Uppercase Letter

Value	Count	Frequency (%)
S	4758	95.4%
I	134	2.7%
H	72	1.4%
P	22	0.4%

Space Separator

Value	Count	Frequency (%)
	22	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	40048	99.9%
Common	22	0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	9584	23.9%
d	9584	23.9%
t	5026	12.5%
r	4914	12.3%
n	4859	12.1%
S	4758	11.9%
e	424	1.1%
i	228	0.6%
m	178	0.4%
I	134	0.3%
Other values (8)	359	0.9%

Common

Value	Count	Frequency (%)
	22	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	40070	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	9584	23.9%
d	9584	23.9%
t	5026	12.5%
r	4914	12.3%
n	4859	12.1%
S	4758	11.9%
e	424	1.1%
i	228	0.6%
m	178	0.4%
I	134	0.3%
Other values (9)	381	1.0%

Vehicle_New_Cost_Amount
Real number (ℝ)

Distinct	32
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	263.0012087

Minimum	-1
Maximum	45000
Zeros	7
Zeros (%)	0.1%
Negative	4883
Negative (%)	98.4%
Memory size	38.9 KiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	-1
median	-1
Q3	-1
95-th percentile	-1
Maximum	45000
Range	45001
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2418.717194
Coefficient of variation (CV)	9.196601055
Kurtosis	118.7991215
Mean	263.0012087
Median Absolute Deviation (MAD)	0
Skewness	10.39626324
Sum	1305538
Variance	5850192.862
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=32)

Value	Count	Frequency (%)
-1	4883	98.4%
0	7	0.1%
25000	6	0.1%
15000	6	0.1%
30000	5	0.1%
10000	5	0.1%
20000	5	0.1%
16000	5	0.1%
12000	4	0.1%
8000	4	0.1%
Other values (22)	34	0.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	4883	98.4%
0	7	0.1%
2	1	< 0.1%
19	1	< 0.1%
2000	1	< 0.1%
3000	2	< 0.1%
3500	1	< 0.1%
4000	1	< 0.1%
4400	1	< 0.1%
6000	1	< 0.1%

Value	Count	Frequency (%)
45000	1	< 0.1%
40000	1	< 0.1%
32000	1	< 0.1%
30000	5	0.1%
28500	1	< 0.1%
28000	2	< 0.1%
26000	2	< 0.1%
25000	6	0.1%
24000	4	0.1%
23000	1	< 0.1%

Vehicle_Symbol
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	25
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.2520145

Minimum	1
Maximum	26
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	1
5-th percentile	5
Q1	8
median	11
Q3	14
95-th percentile	18
Maximum	26
Range	25
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.046817738
Coefficient of variation (CV)	0.3596527303
Kurtosis	-0.02118968875
Mean	11.2520145
Median Absolute Deviation (MAD)	3
Skewness	0.229020055
Sum	55855
Variance	16.3767338
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
11	570	11.5%
10	561	11.3%
8	535	10.8%
12	483	9.7%
14	447	9.0%
13	405	8.2%
7	346	7.0%
15	312	6.3%
6	251	5.1%
16	243	4.9%
Other values (15)	811	16.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	5	0.1%
2	29	0.6%
3	43	0.9%
4	122	2.5%
5	171	3.4%
6	251	5.1%
7	346	7.0%
8	535	10.8%
10	561	11.3%
11	570	11.5%

Value	Count	Frequency (%)
26	5	0.1%
25	3	0.1%
24	5	0.1%
23	11	0.2%
22	34	0.7%
21	35	0.7%
20	48	1.0%
19	61	1.2%
18	102	2.1%
17	137	2.8%

Vehicle_Number_Of_Drivers_Assigned
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

1	3464
99	1399
2	94
3	6
4	1

Length

Max length	2
Median length	1
Mean length	1.28182917
Min length	1

Characters and Unicode

Total characters	6363
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	1
2nd row	1
3rd row	99
4th row	99
5th row	1

Common Values

Value	Count	Frequency (%)
1	3464	69.8%
99	1399	28.2%
2	94	1.9%
3	6	0.1%
4	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	3464	69.8%
99	1399	28.2%
2	94	1.9%
3	6	0.1%
4	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
1	3464	54.4%
9	2798	44.0%
2	94	1.5%
3	6	0.1%
4	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	6363	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	3464	54.4%
9	2798	44.0%
2	94	1.5%
3	6	0.1%
4	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	6363	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	3464	54.4%
9	2798	44.0%
2	94	1.5%
3	6	0.1%
4	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6363	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	3464	54.4%
9	2798	44.0%
2	94	1.5%
3	6	0.1%
4	1	< 0.1%

Vehicle_Usage
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Pleasure	2659
Work	1824
Farm	459
Business	22

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	39712
Distinct characters	16
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Pleasure
2nd row	Pleasure
3rd row	Farm
4th row	Pleasure
5th row	Pleasure

Common Values

Value	Count	Frequency (%)
Pleasure	2659	53.6%
Work	1824	36.7%
Farm	459	9.2%
Business	22	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
pleasure	2659	53.6%
work	1824	36.7%
farm	459	9.2%
business	22	0.4%

Most occurring characters

Value	Count	Frequency (%)
	9132	23.0%
e	5340	13.4%
r	4942	12.4%
a	3118	7.9%
s	2725	6.9%
u	2681	6.8%
P	2659	6.7%
l	2659	6.7%
W	1824	4.6%
o	1824	4.6%
Other values (6)	2808	7.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	25616	64.5%
Space Separator	9132	23.0%
Uppercase Letter	4964	12.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	5340	20.8%
r	4942	19.3%
a	3118	12.2%
s	2725	10.6%
u	2681	10.5%
l	2659	10.4%
o	1824	7.1%
k	1824	7.1%
m	459	1.8%
i	22	0.1%

Uppercase Letter

Value	Count	Frequency (%)
P	2659	53.6%
W	1824	36.7%
F	459	9.2%
B	22	0.4%

Space Separator

Value	Count	Frequency (%)
	9132	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	30580	77.0%
Common	9132	23.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	5340	17.5%
r	4942	16.2%
a	3118	10.2%
s	2725	8.9%
u	2681	8.8%
P	2659	8.7%
l	2659	8.7%
W	1824	6.0%
o	1824	6.0%
k	1824	6.0%
Other values (5)	984	3.2%

Common

Value	Count	Frequency (%)
	9132	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	39712	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	9132	23.0%
e	5340	13.4%
r	4942	12.4%
a	3118	7.9%
s	2725	6.9%
u	2681	6.8%
P	2659	6.7%
l	2659	6.7%
W	1824	4.6%
o	1824	4.6%
Other values (6)	2808	7.1%

Vehicle_Miles_To_Work
Real number (ℝ)

HIGH CORRELATION

Distinct	44
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.253021757

Minimum	-1
Maximum	70
Zeros	9
Zeros (%)	0.2%
Negative	3107
Negative (%)	62.6%
Memory size	38.9 KiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	-1
median	-1
Q3	6
95-th percentile	15
Maximum	70
Range	71
Interquartile range (IQR)	7

Descriptive statistics

Standard deviation	7.516818468
Coefficient of variation (CV)	2.310718781
Kurtosis	12.38461536
Mean	3.253021757
Median Absolute Deviation (MAD)	0
Skewness	2.878665537
Sum	16148
Variance	56.50255988
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=44)

Value	Count	Frequency (%)
-1	3107	62.6%
10	362	7.3%
5	224	4.5%
12	166	3.3%
8	131	2.6%
6	106	2.1%
3	105	2.1%
14	104	2.1%
4	88	1.8%
2	74	1.5%
Other values (34)	497	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	3107	62.6%
0	9	0.2%
1	53	1.1%
2	74	1.5%
3	105	2.1%
4	88	1.8%
5	224	4.5%
6	106	2.1%
7	74	1.5%
8	131	2.6%

Value	Count	Frequency (%)
70	2	< 0.1%
63	1	< 0.1%
60	1	< 0.1%
55	1	< 0.1%
53	1	< 0.1%
50	15	0.3%
48	1	< 0.1%
45	6	0.1%
42	1	< 0.1%
40	10	0.2%

Vehicle_Days_Per_Week_Driven
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

5	4963
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	5
2nd row	5
3rd row	5
4th row	5
5th row	5

Common Values

Value	Count	Frequency (%)
5	4963	> 99.9%
1	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
5	4963	> 99.9%
1	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
5	4963	> 99.9%
1	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
5	4963	> 99.9%
1	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
5	4963	> 99.9%
1	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
5	4963	> 99.9%
1	1	< 0.1%

Vehicle_Annual_Miles
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Unknown	4962
0	2

Length

Max length	7
Median length	7
Mean length	6.997582595
Min length	1

Characters and Unicode

Total characters	34736
Distinct characters	6
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Unknown
2nd row	Unknown
3rd row	Unknown
4th row	Unknown
5th row	Unknown

Common Values

Value	Count	Frequency (%)
Unknown	4962	> 99.9%
0	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
unknown	4962	> 99.9%
0	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
n	14886	42.9%
U	4962	14.3%
k	4962	14.3%
o	4962	14.3%
w	4962	14.3%
0	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	29772	85.7%
Uppercase Letter	4962	14.3%
Decimal Number	2	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	14886	50.0%
k	4962	16.7%
o	4962	16.7%
w	4962	16.7%

Uppercase Letter

Value	Count	Frequency (%)
U	4962	100.0%

Decimal Number

Value	Count	Frequency (%)
0	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	34734	> 99.9%
Common	2	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	14886	42.9%
U	4962	14.3%
k	4962	14.3%
o	4962	14.3%
w	4962	14.3%

Common

Value	Count	Frequency (%)
0	2	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	34736	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	14886	42.9%
U	4962	14.3%
k	4962	14.3%
o	4962	14.3%
w	4962	14.3%
0	2	< 0.1%

Vehicle_Anti_Theft_Device
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Not Applicable	2902
Passive Disabling-Vehicle Recovery	1563
Alarm Only	390
Active Disabling	109

Length

Max length	34
Median length	14
Mean length	20.02699436
Min length	10

Characters and Unicode

Total characters	99414
Distinct characters	26
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Not Applicable
2nd row	Not Applicable
3rd row	Not Applicable
4th row	Not Applicable
5th row	Not Applicable

Common Values

Value	Count	Frequency (%)
Not Applicable	2902	58.5%
Passive Disabling-Vehicle Recovery	1563	31.5%
Alarm Only	390	7.9%
Active Disabling	109	2.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
not	2902	25.3%
applicable	2902	25.3%
passive	1563	13.6%
disabling-vehicle	1563	13.6%
recovery	1563	13.6%
alarm	390	3.4%
only	390	3.4%
active	109	0.9%
disabling	109	0.9%

Most occurring characters

Value	Count	Frequency (%)
e	10826	10.9%
l	9819	9.9%
i	9481	9.5%
	6527	6.6%
a	6527	6.6%
c	6137	6.2%
p	5804	5.8%
s	4798	4.8%
b	4574	4.6%
o	4465	4.5%
Other values (16)	30456	30.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	78270	78.7%
Uppercase Letter	13054	13.1%
Space Separator	6527	6.6%
Dash Punctuation	1563	1.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	10826	13.8%
l	9819	12.5%
i	9481	12.1%
a	6527	8.3%
c	6137	7.8%
p	5804	7.4%
s	4798	6.1%
b	4574	5.8%
o	4465	5.7%
v	3235	4.1%
Other values (7)	12604	16.1%

Uppercase Letter

Value	Count	Frequency (%)
A	3401	26.1%
N	2902	22.2%
D	1672	12.8%
P	1563	12.0%
V	1563	12.0%
R	1563	12.0%
O	390	3.0%

Space Separator

Value	Count	Frequency (%)
	6527	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	1563	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	91324	91.9%
Common	8090	8.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	10826	11.9%
l	9819	10.8%
i	9481	10.4%
a	6527	7.1%
c	6137	6.7%
p	5804	6.4%
s	4798	5.3%
b	4574	5.0%
o	4465	4.9%
A	3401	3.7%
Other values (14)	25492	27.9%

Common

Value	Count	Frequency (%)
	6527	80.7%
-	1563	19.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	99414	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	10826	10.9%
l	9819	9.9%
i	9481	9.5%
	6527	6.6%
a	6527	6.6%
c	6137	6.2%
p	5804	5.8%
s	4798	4.8%
b	4574	4.6%
o	4465	4.5%
Other values (16)	30456	30.6%

Vehicle_Passive_Restraint
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Y	3648
N	1314
Unknown	2

Length

Max length	7
Median length	1
Mean length	1.002417405
Min length	1

Characters and Unicode

Total characters	4976
Distinct characters	7
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	N
2nd row	Y
3rd row	N
4th row	Y
5th row	N

Common Values

Value	Count	Frequency (%)
Y	3648	73.5%
N	1314	26.5%
Unknown	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
y	3648	73.5%
n	1314	26.5%
unknown	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
Y	3648	73.3%
N	1314	26.4%
n	6	0.1%
U	2	< 0.1%
k	2	< 0.1%
o	2	< 0.1%
w	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	4964	99.8%
Lowercase Letter	12	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	6	50.0%
k	2	16.7%
o	2	16.7%
w	2	16.7%

Uppercase Letter

Value	Count	Frequency (%)
Y	3648	73.5%
N	1314	26.5%
U	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4976	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
Y	3648	73.3%
N	1314	26.4%
n	6	0.1%
U	2	< 0.1%
k	2	< 0.1%
o	2	< 0.1%
w	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4976	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
Y	3648	73.3%
N	1314	26.4%
n	6	0.1%
U	2	< 0.1%
k	2	< 0.1%
o	2	< 0.1%
w	2	< 0.1%

Vehicle_Age_In_Years
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.067284448

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	9
Q3	9
95-th percentile	9
Maximum	9
Range	8
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.577883233
Coefficient of variation (CV)	0.3647629089
Kurtosis	-0.3812779045
Mean	7.067284448
Median Absolute Deviation (MAD)	0
Skewness	-1.023117
Sum	35082
Variance	6.645481965
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
9	2682	54.0%
7	360	7.3%
8	305	6.1%
6	300	6.0%
5	294	5.9%
4	284	5.7%
3	282	5.7%
2	275	5.5%
1	182	3.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	182	3.7%
2	275	5.5%
3	282	5.7%
4	284	5.7%
5	294	5.9%
6	300	6.0%
7	360	7.3%
8	305	6.1%
9	2682	54.0%

Value	Count	Frequency (%)
9	2682	54.0%
8	305	6.1%
7	360	7.3%
6	300	6.0%
5	294	5.9%
4	284	5.7%
3	282	5.7%
2	275	5.5%
1	182	3.7%

Vehicle_Med_Pay_Limit
Real number (ℝ)

Distinct	7
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2945.563457

Minimum	-1
Maximum	50000
Zeros	0
Zeros (%)	0.0%
Negative	1223
Negative (%)	24.6%
Memory size	38.9 KiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	1000
median	1000
Q3	5000
95-th percentile	10000
Maximum	50000
Range	50001
Interquartile range (IQR)	4000

Descriptive statistics

Standard deviation	6826.446262
Coefficient of variation (CV)	2.317534951
Kurtosis	34.89778382
Mean	2945.563457
Median Absolute Deviation (MAD)	1001
Skewness	5.652149498
Sum	14621777
Variance	46600368.57
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
1000	2209	44.5%
-1	1223	24.6%
5000	1126	22.7%
2000	147	3.0%
10000	134	2.7%
50000	81	1.6%
25000	44	0.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	1223	24.6%
1000	2209	44.5%
2000	147	3.0%
5000	1126	22.7%
10000	134	2.7%
25000	44	0.9%
50000	81	1.6%

Value	Count	Frequency (%)
50000	81	1.6%
25000	44	0.9%
10000	134	2.7%
5000	1126	22.7%
2000	147	3.0%
1000	2209	44.5%
-1	1223	24.6%

Vehicle_Bodily_Injury_Limit
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	7
Distinct (%)	0.1%
Missing	194
Missing (%)	3.9%
Memory size	38.9 KiB

25-50	1706
100-300	1590
50-100	1210
250-500	239
300-500	11
Other values (2)	14

Length

Max length	7
Median length	7
Mean length	7
Min length	7

Characters and Unicode

Total characters	33390
Distinct characters	7
Distinct categories	3 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	25-50
2nd row	25-50
3rd row	250-500
4th row	100-300
5th row	25-50

Common Values

Value	Count	Frequency (%)
25-50	1706	34.4%
100-300	1590	32.0%
50-100	1210	24.4%
250-500	239	4.8%
300-500	11	0.2%
500-500	10	0.2%
100-500	4	0.1%
(Missing)	194	3.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
25-50	1706	35.8%
100-300	1590	33.3%
50-100	1210	25.4%
250-500	239	5.0%
300-500	11	0.2%
500-500	10	0.2%
100-500	4	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	12513	37.5%
5	5135	15.4%
-	4770	14.3%
	4622	13.8%
1	2804	8.4%
2	1945	5.8%
3	1601	4.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	23998	71.9%
Dash Punctuation	4770	14.3%
Space Separator	4622	13.8%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	12513	52.1%
5	5135	21.4%
1	2804	11.7%
2	1945	8.1%
3	1601	6.7%

Dash Punctuation

Value	Count	Frequency (%)
-	4770	100.0%

Space Separator

Value	Count	Frequency (%)
	4622	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	33390	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	12513	37.5%
5	5135	15.4%
-	4770	14.3%
	4622	13.8%
1	2804	8.4%
2	1945	5.8%
3	1601	4.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	33390	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	12513	37.5%
5	5135	15.4%
-	4770	14.3%
	4622	13.8%
1	2804	8.4%
2	1945	5.8%
3	1601	4.8%

Vehicle_Physical_Damage_Limit
Real number (ℝ)

HIGH CORRELATION

Distinct	7
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	48251.37107

Minimum	-1
Maximum	500000
Zeros	0
Zeros (%)	0.0%
Negative	194
Negative (%)	3.9%
Memory size	38.9 KiB

Quantile statistics

Minimum	-1
5-th percentile	25000
Q1	25000
median	50000
Q3	50000
95-th percentile	100000
Maximum	500000
Range	500001
Interquartile range (IQR)	25000

Descriptive statistics

Standard deviation	37679.7618
Coefficient of variation (CV)	0.7809055155
Kurtosis	45.98639559
Mean	48251.37107
Median Absolute Deviation (MAD)	25000
Skewness	4.922716924
Sum	239519806
Variance	1419764449
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
50000	1967	39.6%
25000	1718	34.6%
100000	723	14.6%
35000	312	6.3%
-1	194	3.9%
250000	40	0.8%
500000	10	0.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	194	3.9%
25000	1718	34.6%
35000	312	6.3%
50000	1967	39.6%
100000	723	14.6%
250000	40	0.8%
500000	10	0.2%

Value	Count	Frequency (%)
500000	10	0.2%
250000	40	0.8%
100000	723	14.6%
50000	1967	39.6%
35000	312	6.3%
25000	1718	34.6%
-1	194	3.9%

Vehicle_Comprehensive_Coverage_Indicator
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

False	4776
True	188

Common Values
Chart

Value	Count	Frequency (%)
False	4776	96.2%
True	188	3.8%

Vehicle_Comprehensive_Coverage_Limit
Real number (ℝ)

HIGH CORRELATION

Distinct	7
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6158.385173

Minimum	-1
Maximum	1000000
Zeros	0
Zeros (%)	0.0%
Negative	4776
Negative (%)	96.2%
Memory size	38.9 KiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	-1
median	-1
Q3	-1
95-th percentile	-1
Maximum	1000000
Range	1000001
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	42766.89152
Coefficient of variation (CV)	6.944497675
Kurtosis	138.8361865
Mean	6158.385173
Median Absolute Deviation (MAD)	0
Skewness	10.51994148
Sum	30570224
Variance	1829007010
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
-1	4776	96.2%
75000	81	1.6%
100000	61	1.2%
300000	24	0.5%
500000	20	0.4%
200000	1	< 0.1%
1000000	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	4776	96.2%
75000	81	1.6%
100000	61	1.2%
200000	1	< 0.1%
300000	24	0.5%
500000	20	0.4%
1000000	1	< 0.1%

Value	Count	Frequency (%)
1000000	1	< 0.1%
500000	20	0.4%
300000	24	0.5%
200000	1	< 0.1%
100000	61	1.2%
75000	81	1.6%
-1	4776	96.2%

Vehicle_Collision_Coverage_Indicator
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

True	3005
False	1959

Common Values
Chart

Value	Count	Frequency (%)
True	3005	60.5%
False	1959	39.5%

Vehicle_Collision_Coverage_Deductible
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	294.4582998

Minimum	-1
Maximum	3000
Zeros	0
Zeros (%)	0.0%
Negative	1959
Negative (%)	39.5%
Memory size	38.9 KiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	-1
median	250
Q3	500
95-th percentile	500
Maximum	3000
Range	3001
Interquartile range (IQR)	501

Descriptive statistics

Standard deviation	276.6693375
Coefficient of variation (CV)	0.9395874992
Kurtosis	1.536179161
Mean	294.4582998
Median Absolute Deviation (MAD)	250
Skewness	0.6222835143
Sum	1461691
Variance	76545.9223
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
500	2235	45.0%
-1	1959	39.5%
250	528	10.6%
1000	205	4.1%
100	27	0.5%
200	7	0.1%
50	1	< 0.1%
3000	1	< 0.1%
2000	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-1	1959	39.5%
50	1	< 0.1%
100	27	0.5%
200	7	0.1%
250	528	10.6%
500	2235	45.0%
1000	205	4.1%
2000	1	< 0.1%
3000	1	< 0.1%

Value	Count	Frequency (%)
3000	1	< 0.1%
2000	1	< 0.1%
1000	205	4.1%
500	2235	45.0%
250	528	10.6%
200	7	0.1%
100	27	0.5%
50	1	< 0.1%
-1	1959	39.5%

Driver_Total
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

1	4368
2	595
3	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	2

Common Values

Value	Count	Frequency (%)
1	4368	88.0%
2	595	12.0%
3	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	4368	88.0%
2	595	12.0%
3	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
1	4368	88.0%
2	595	12.0%
3	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	4368	88.0%
2	595	12.0%
3	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	4368	88.0%
2	595	12.0%
3	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	4368	88.0%
2	595	12.0%
3	1	< 0.1%

Driver_Total_Male
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

1	2626
0	2311
2	27

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	2626	52.9%
0	2311	46.6%
2	27	0.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	2626	52.9%
0	2311	46.6%
2	27	0.5%

Most occurring characters

Value	Count	Frequency (%)
1	2626	52.9%
0	2311	46.6%
2	27	0.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	2626	52.9%
0	2311	46.6%
2	27	0.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	2626	52.9%
0	2311	46.6%
2	27	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	2626	52.9%
0	2311	46.6%
2	27	0.5%

Driver_Total_Female
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

1	2799
0	2124
2	41

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
1	2799	56.4%
0	2124	42.8%
2	41	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	2799	56.4%
0	2124	42.8%
2	41	0.8%

Most occurring characters

Value	Count	Frequency (%)
1	2799	56.4%
0	2124	42.8%
2	41	0.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	2799	56.4%
0	2124	42.8%
2	41	0.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	2799	56.4%
0	2124	42.8%
2	41	0.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	2799	56.4%
0	2124	42.8%
2	41	0.8%

Driver_Total_Single
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	3796
1	1148
2	20

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	3796	76.5%
1	1148	23.1%
2	20	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	3796	76.5%
1	1148	23.1%
2	20	0.4%

Most occurring characters

Value	Count	Frequency (%)
0	3796	76.5%
1	1148	23.1%
2	20	0.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3796	76.5%
1	1148	23.1%
2	20	0.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3796	76.5%
1	1148	23.1%
2	20	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3796	76.5%
1	1148	23.1%
2	20	0.4%

Driver_Total_Married
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

1	2554
0	1940
2	470

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	2

Common Values

Value	Count	Frequency (%)
1	2554	51.5%
0	1940	39.1%
2	470	9.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	2554	51.5%
0	1940	39.1%
2	470	9.5%

Most occurring characters

Value	Count	Frequency (%)
1	2554	51.5%
0	1940	39.1%
2	470	9.5%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	2554	51.5%
0	1940	39.1%
2	470	9.5%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	2554	51.5%
0	1940	39.1%
2	470	9.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	2554	51.5%
0	1940	39.1%
2	470	9.5%

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

1	3801
0	1158
2	5

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	3801	76.6%
0	1158	23.3%
2	5	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	3801	76.6%
0	1158	23.3%
2	5	0.1%

Most occurring characters

Value	Count	Frequency (%)
1	3801	76.6%
0	1158	23.3%
2	5	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	3801	76.6%
0	1158	23.3%
2	5	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	3801	76.6%
0	1158	23.3%
2	5	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	3801	76.6%
0	1158	23.3%
2	5	0.1%

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	3693
1	1270
2	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	3693	74.4%
1	1270	25.6%
2	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	3693	74.4%
1	1270	25.6%
2	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	3693	74.4%
1	1270	25.6%
2	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3693	74.4%
1	1270	25.6%
2	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3693	74.4%
1	1270	25.6%
2	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3693	74.4%
1	1270	25.6%
2	1	< 0.1%

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	4602
1	359
2	3

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4602	92.7%
1	359	7.2%
2	3	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	4602	92.7%
1	359	7.2%
2	3	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	4602	92.7%
1	359	7.2%
2	3	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4602	92.7%
1	359	7.2%
2	3	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4602	92.7%
1	359	7.2%
2	3	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4602	92.7%
1	359	7.2%
2	3	0.1%

Driver_Total_Licensed_In_State
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

1	4359
2	592
0	12
3	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	1
2nd row	1
3rd row	1
4th row	1
5th row	2

Common Values

Value	Count	Frequency (%)
1	4359	87.8%
2	592	11.9%
0	12	0.2%
3	1	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	4359	87.8%
2	592	11.9%
0	12	0.2%
3	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
1	4359	87.8%
2	592	11.9%
0	12	0.2%
3	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	4359	87.8%
2	592	11.9%
0	12	0.2%
3	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	4359	87.8%
2	592	11.9%
0	12	0.2%
3	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	4359	87.8%
2	592	11.9%
0	12	0.2%
3	1	< 0.1%

Driver_Minimum_Age
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	77
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	46.08843674

Minimum	16
Maximum	93
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	16
5-th percentile	20
Q1	35
median	46
Q3	57
95-th percentile	73
Maximum	93
Range	77
Interquartile range (IQR)	22

Descriptive statistics

Standard deviation	15.8180783
Coefficient of variation (CV)	0.3432114304
Kurtosis	-0.4738025737
Mean	46.08843674
Median Absolute Deviation (MAD)	11
Skewness	0.2218588281
Sum	228783
Variance	250.2116011
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
41	141	2.8%
39	132	2.7%
51	128	2.6%
49	119	2.4%
48	119	2.4%
45	118	2.4%
47	115	2.3%
46	114	2.3%
35	114	2.3%
44	112	2.3%
Other values (67)	3752	75.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
16	38	0.8%
17	45	0.9%
18	54	1.1%
19	69	1.4%
20	50	1.0%
21	56	1.1%
22	45	0.9%
23	50	1.0%
24	54	1.1%
25	69	1.4%

Value	Count	Frequency (%)
93	1	< 0.1%
91	3	0.1%
90	2	< 0.1%
89	4	0.1%
88	4	0.1%
87	8	0.2%
86	10	0.2%
85	12	0.2%
84	11	0.2%
83	17	0.3%

Driver_Maximum_Age
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	77
Distinct (%)	1.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	47.02921031

Minimum	16
Maximum	93
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	16
5-th percentile	21
Q1	36
median	47
Q3	58
95-th percentile	74
Maximum	93
Range	77
Interquartile range (IQR)	22

Descriptive statistics

Standard deviation	15.59354762
Coefficient of variation (CV)	0.3315715386
Kurtosis	-0.4507331482
Mean	47.02921031
Median Absolute Deviation (MAD)	11
Skewness	0.2057878855
Sum	233453
Variance	243.1587275
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
41	144	2.9%
39	139	2.8%
49	132	2.7%
51	132	2.7%
48	126	2.5%
45	123	2.5%
52	123	2.5%
43	119	2.4%
42	115	2.3%
35	114	2.3%
Other values (67)	3697	74.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
16	27	0.5%
17	32	0.6%
18	40	0.8%
19	59	1.2%
20	42	0.8%
21	50	1.0%
22	42	0.8%
23	45	0.9%
24	51	1.0%
25	59	1.2%

Value	Count	Frequency (%)
93	1	< 0.1%
91	4	0.1%
90	2	< 0.1%
89	4	0.1%
88	4	0.1%
87	8	0.2%
86	10	0.2%
85	12	0.2%
84	11	0.2%
83	17	0.3%

Driver_Total_Teenager_Age_15_19
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	4758
1	204
2	2

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4758	95.9%
1	204	4.1%
2	2	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	4758	95.9%
1	204	4.1%
2	2	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	4758	95.9%
1	204	4.1%
2	2	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4758	95.9%
1	204	4.1%
2	2	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4758	95.9%
1	204	4.1%
2	2	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4758	95.9%
1	204	4.1%
2	2	< 0.1%

Driver_Total_College_Ages_20_23
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	4761
1	199
2	4

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4761	95.9%
1	199	4.0%
2	4	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	4761	95.9%
1	199	4.0%
2	4	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	4761	95.9%
1	199	4.0%
2	4	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4761	95.9%
1	199	4.0%
2	4	0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4761	95.9%
1	199	4.0%
2	4	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4761	95.9%
1	199	4.0%
2	4	0.1%

Driver_Total_Young_Adult_Ages_24_29
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	4539
1	390
2	35

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4539	91.4%
1	390	7.9%
2	35	0.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	4539	91.4%
1	390	7.9%
2	35	0.7%

Most occurring characters

Value	Count	Frequency (%)
0	4539	91.4%
1	390	7.9%
2	35	0.7%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4539	91.4%
1	390	7.9%
2	35	0.7%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4539	91.4%
1	390	7.9%
2	35	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4539	91.4%
1	390	7.9%
2	35	0.7%

Driver_Total_Low_Middle_Adult_Ages_30_39
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	3959
1	944
2	61

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	1
5th row	0

Common Values

Value	Count	Frequency (%)
0	3959	79.8%
1	944	19.0%
2	61	1.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	3959	79.8%
1	944	19.0%
2	61	1.2%

Most occurring characters

Value	Count	Frequency (%)
0	3959	79.8%
1	944	19.0%
2	61	1.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3959	79.8%
1	944	19.0%
2	61	1.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3959	79.8%
1	944	19.0%
2	61	1.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3959	79.8%
1	944	19.0%
2	61	1.2%

Driver_Total_Middle_Adult_Ages_40_49
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	3720
1	1175
2	69

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	1
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	3720	74.9%
1	1175	23.7%
2	69	1.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	3720	74.9%
1	1175	23.7%
2	69	1.4%

Most occurring characters

Value	Count	Frequency (%)
0	3720	74.9%
1	1175	23.7%
2	69	1.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3720	74.9%
1	1175	23.7%
2	69	1.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3720	74.9%
1	1175	23.7%
2	69	1.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3720	74.9%
1	1175	23.7%
2	69	1.4%

Driver_Total_Adult_Ages_50_64
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	3514
1	1339
2	111

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	3514	70.8%
1	1339	27.0%
2	111	2.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	3514	70.8%
1	1339	27.0%
2	111	2.2%

Most occurring characters

Value	Count	Frequency (%)
0	3514	70.8%
1	1339	27.0%
2	111	2.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3514	70.8%
1	1339	27.0%
2	111	2.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3514	70.8%
1	1339	27.0%
2	111	2.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3514	70.8%
1	1339	27.0%
2	111	2.2%

Driver_Total_Senior_Ages_65_69
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	4666
1	285
2	13

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4666	94.0%
1	285	5.7%
2	13	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	4666	94.0%
1	285	5.7%
2	13	0.3%

Most occurring characters

Value	Count	Frequency (%)
0	4666	94.0%
1	285	5.7%
2	13	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4666	94.0%
1	285	5.7%
2	13	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4666	94.0%
1	285	5.7%
2	13	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4666	94.0%
1	285	5.7%
2	13	0.3%

Driver_Total_Upper_Senior_Ages_70_plus
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	4550
1	393
2	21

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4550	91.7%
1	393	7.9%
2	21	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	4550	91.7%
1	393	7.9%
2	21	0.4%

Most occurring characters

Value	Count	Frequency (%)
0	4550	91.7%
1	393	7.9%
2	21	0.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4550	91.7%
1	393	7.9%
2	21	0.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4550	91.7%
1	393	7.9%
2	21	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4550	91.7%
1	393	7.9%
2	21	0.4%

Vehicle_Youthful_Driver_Indicator
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

False	4478
True	486

Common Values
Chart

Value	Count	Frequency (%)
False	4478	90.2%
True	486	9.8%

Vehicle_Youthful_Driver_Training_Code
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Not Applicable	4478
With or Without Driver Training	233
Without Driver Training	214
With Driver Training	39

Length

Max length	31
Median length	31
Mean length	31
Min length	31

Characters and Unicode

Total characters	153884
Distinct characters	21
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Not Applicable
2nd row	Not Applicable
3rd row	Not Applicable
4th row	Not Applicable
5th row	Not Applicable

Common Values

Value	Count	Frequency (%)
Not Applicable	4478	90.2%
With or Without Driver Training	233	4.7%
Without Driver Training	214	4.3%
With Driver Training	39	0.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
not	4478	41.2%
applicable	4478	41.2%
training	486	4.5%
driver	486	4.5%
without	447	4.1%
with	272	2.5%
or	233	2.1%

Most occurring characters

Value	Count	Frequency (%)
	84183	54.7%
p	8956	5.8%
l	8956	5.8%
i	6655	4.3%
t	5644	3.7%
o	5158	3.4%
a	4964	3.2%
e	4964	3.2%
N	4478	2.9%
A	4478	2.9%
Other values (11)	15448	10.0%

Most occurring categories

Value	Count	Frequency (%)
Space Separator	84183	54.7%
Lowercase Letter	59054	38.4%
Uppercase Letter	10647	6.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
p	8956	15.2%
l	8956	15.2%
i	6655	11.3%
t	5644	9.6%
o	5158	8.7%
a	4964	8.4%
e	4964	8.4%
c	4478	7.6%
b	4478	7.6%
r	1691	2.9%
Other values (5)	3110	5.3%

Uppercase Letter

Value	Count	Frequency (%)
N	4478	42.1%
A	4478	42.1%
W	719	6.8%
D	486	4.6%
T	486	4.6%

Space Separator

Value	Count	Frequency (%)
	84183	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	84183	54.7%
Latin	69701	45.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
p	8956	12.8%
l	8956	12.8%
i	6655	9.5%
t	5644	8.1%
o	5158	7.4%
a	4964	7.1%
e	4964	7.1%
N	4478	6.4%
A	4478	6.4%
c	4478	6.4%
Other values (10)	10970	15.7%

Common

Value	Count	Frequency (%)
	84183	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	153884	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	84183	54.7%
p	8956	5.8%
l	8956	5.8%
i	6655	4.3%
t	5644	3.7%
o	5158	3.4%
a	4964	3.2%
e	4964	3.2%
N	4478	2.9%
A	4478	2.9%
Other values (11)	15448	10.0%

Vehicle_Youthful_Good_Student_Code
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Not Eligible for Good Student Credit	4902
Eligible for Good Student Credit	62

Length

Max length	36
Median length	36
Mean length	36
Min length	36

Characters and Unicode

Total characters	178704
Distinct characters	18
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Not Eligible for Good Student Credit
2nd row	Not Eligible for Good Student Credit
3rd row	Not Eligible for Good Student Credit
4th row	Not Eligible for Good Student Credit
5th row	Not Eligible for Good Student Credit

Common Values

Value	Count	Frequency (%)
Not Eligible for Good Student Credit	4902	98.8%
Eligible for Good Student Credit	62	1.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
for	4964	16.7%
credit	4964	16.7%
good	4964	16.7%
student	4964	16.7%
eligible	4964	16.7%
not	4902	16.5%

Most occurring characters

Value	Count	Frequency (%)
	25006	14.0%
o	19794	11.1%
t	19794	11.1%
i	14892	8.3%
e	14892	8.3%
d	14892	8.3%
l	9928	5.6%
r	9928	5.6%
E	4964	2.8%
g	4964	2.8%
Other values (8)	39650	22.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	128940	72.2%
Space Separator	25006	14.0%
Uppercase Letter	24758	13.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	19794	15.4%
t	19794	15.4%
i	14892	11.5%
e	14892	11.5%
d	14892	11.5%
l	9928	7.7%
r	9928	7.7%
g	4964	3.8%
b	4964	3.8%
f	4964	3.8%
Other values (2)	9928	7.7%

Uppercase Letter

Value	Count	Frequency (%)
E	4964	20.1%
G	4964	20.1%
S	4964	20.1%
C	4964	20.1%
N	4902	19.8%

Space Separator

Value	Count	Frequency (%)
	25006	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	153698	86.0%
Common	25006	14.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	19794	12.9%
t	19794	12.9%
i	14892	9.7%
e	14892	9.7%
d	14892	9.7%
l	9928	6.5%
r	9928	6.5%
E	4964	3.2%
g	4964	3.2%
b	4964	3.2%
Other values (7)	34686	22.6%

Common

Value	Count	Frequency (%)
	25006	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	178704	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	25006	14.0%
o	19794	11.1%
t	19794	11.1%
i	14892	8.3%
e	14892	8.3%
d	14892	8.3%
l	9928	5.6%
r	9928	5.6%
E	4964	2.8%
g	4964	2.8%
Other values (8)	39650	22.2%

Vehicle_Driver_Points
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	4442
1	441
2	72
3	9

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4442	89.5%
1	441	8.9%
2	72	1.5%
3	9	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	4442	89.5%
1	441	8.9%
2	72	1.5%
3	9	0.2%

Most occurring characters

Value	Count	Frequency (%)
0	4442	89.5%
1	441	8.9%
2	72	1.5%
3	9	0.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4442	89.5%
1	441	8.9%
2	72	1.5%
3	9	0.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4442	89.5%
1	441	8.9%
2	72	1.5%
3	9	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4442	89.5%
1	441	8.9%
2	72	1.5%
3	9	0.2%

Vehicle_Safe_Driver_Discount_Indicator
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

True	2927
False	2037

Common Values
Chart

Value	Count	Frequency (%)
True	2927	59.0%
False	2037	41.0%

EEA_Liability_Coverage_Only_Indicator
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

False	3602
True	1362

Common Values
Chart

Value	Count	Frequency (%)
False	3602	72.6%
True	1362	27.4%

EEA_Multi_Auto_Policies_Indicator
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

True	4384
False	580

Common Values
Chart

Value	Count	Frequency (%)
True	4384	88.3%
False	580	11.7%

EEA_Policy_Zip_Code_3
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	27
Distinct (%)	0.5%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

428	628
430	547
424	497
429	403
433	341
Other values (22)	2548

Length

Max length	7
Median length	3
Mean length	3.021756648
Min length	3

Characters and Unicode

Total characters	15000
Distinct characters	15
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	0.1%

Sample

1st row	426
2nd row	428
3rd row	429
4th row	430
5th row	424

Common Values

Value	Count	Frequency (%)
428	628	12.7%
430	547	11.0%
424	497	10.0%
429	403	8.1%
433	341	6.9%
425	330	6.6%
441	281	5.7%
438	279	5.6%
439	231	4.7%
427	226	4.6%
Other values (17)	1201	24.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
428	628	12.7%
430	547	11.0%
424	497	10.0%
429	403	8.1%
433	341	6.9%
425	330	6.6%
441	281	5.7%
438	279	5.6%
439	231	4.7%
427	226	4.6%
Other values (17)	1201	24.2%

Most occurring characters

Value	Count	Frequency (%)
4	5946	39.6%
2	2620	17.5%
3	2465	16.4%
8	908	6.1%
0	687	4.6%
9	634	4.2%
1	526	3.5%
5	489	3.3%
6	272	1.8%
7	264	1.8%
Other values (5)	189	1.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	14811	98.7%
Lowercase Letter	162	1.1%
Uppercase Letter	27	0.2%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
4	5946	40.1%
2	2620	17.7%
3	2465	16.6%
8	908	6.1%
0	687	4.6%
9	634	4.3%
1	526	3.6%
5	489	3.3%
6	272	1.8%
7	264	1.8%

Lowercase Letter

Value	Count	Frequency (%)
n	81	50.0%
k	27	16.7%
o	27	16.7%
w	27	16.7%

Uppercase Letter

Value	Count	Frequency (%)
U	27	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	14811	98.7%
Latin	189	1.3%

Most frequent character per script

Common

Value	Count	Frequency (%)
4	5946	40.1%
2	2620	17.7%
3	2465	16.6%
8	908	6.1%
0	687	4.6%
9	634	4.3%
1	526	3.6%
5	489	3.3%
6	272	1.8%
7	264	1.8%

Latin

Value	Count	Frequency (%)
n	81	42.9%
U	27	14.3%
k	27	14.3%
o	27	14.3%
w	27	14.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	15000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
4	5946	39.6%
2	2620	17.5%
3	2465	16.4%
8	908	6.1%
0	687	4.6%
9	634	4.2%
1	526	3.5%
5	489	3.3%
6	272	1.8%
7	264	1.8%
Other values (5)	189	1.3%

EEA_Policy_Tenure
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	285
Distinct (%)	5.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.686603546

Minimum	0
Maximum	46.9
Zeros	459
Zeros (%)	9.2%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1.2
median	3.5
Q3	8
95-th percentile	19.47
Maximum	46.9
Range	46.9
Interquartile range (IQR)	6.8

Descriptive statistics

Standard deviation	6.450665849
Coefficient of variation (CV)	1.134361803
Kurtosis	5.210895051
Mean	5.686603546
Median Absolute Deviation (MAD)	2.6
Skewness	2.035923485
Sum	28228.3
Variance	41.61108989
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	459	9.2%
0.5	369	7.4%
1	339	6.8%
1.5	273	5.5%
2	273	5.5%
2.5	222	4.5%
3	201	4.0%
3.5	179	3.6%
4	138	2.8%
5	112	2.3%
Other values (275)	2399	48.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	459	9.2%
0.1	2	< 0.1%
0.2	2	< 0.1%
0.3	13	0.3%
0.4	3	0.1%
0.5	369	7.4%
0.6	13	0.3%
0.7	4	0.1%
0.8	15	0.3%
0.9	4	0.1%

Value	Count	Frequency (%)
46.9	1	< 0.1%
46.6	1	< 0.1%
45.2	1	< 0.1%
44.5	1	< 0.1%
44	1	< 0.1%
43.5	1	< 0.1%
41.1	1	< 0.1%
40.8	1	< 0.1%
39.2	1	< 0.1%
37.8	1	< 0.1%

EEA_Agency_Type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

Hybrid	1386
Preferred	1283
Standard	1227
Non-standard	1068

Length

Max length	12
Median length	8
Mean length	8.560636583
Min length	6

Characters and Unicode

Total characters	42495
Distinct characters	17
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Hybrid
2nd row	Standard
3rd row	Non-standard
4th row	Hybrid
5th row	Non-standard

Common Values

Value	Count	Frequency (%)
Hybrid	1386	27.9%
Preferred	1283	25.8%
Standard	1227	24.7%
Non-standard	1068	21.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
hybrid	1386	27.9%
preferred	1283	25.8%
standard	1227	24.7%
non-standard	1068	21.5%

Most occurring characters

Value	Count	Frequency (%)
r	7530	17.7%
d	7259	17.1%
a	4590	10.8%
e	3849	9.1%
n	3363	7.9%
t	2295	5.4%
H	1386	3.3%
y	1386	3.3%
b	1386	3.3%
i	1386	3.3%
Other values (7)	8065	19.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	36463	85.8%
Uppercase Letter	4964	11.7%
Dash Punctuation	1068	2.5%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
r	7530	20.7%
d	7259	19.9%
a	4590	12.6%
e	3849	10.6%
n	3363	9.2%
t	2295	6.3%
y	1386	3.8%
b	1386	3.8%
i	1386	3.8%
f	1283	3.5%
Other values (2)	2136	5.9%

Uppercase Letter

Value	Count	Frequency (%)
H	1386	27.9%
P	1283	25.8%
S	1227	24.7%
N	1068	21.5%

Dash Punctuation

Value	Count	Frequency (%)
-	1068	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	41427	97.5%
Common	1068	2.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
r	7530	18.2%
d	7259	17.5%
a	4590	11.1%
e	3849	9.3%
n	3363	8.1%
t	2295	5.5%
H	1386	3.3%
y	1386	3.3%
b	1386	3.3%
i	1386	3.3%
Other values (6)	6997	16.9%

Common

Value	Count	Frequency (%)
-	1068	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	42495	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
r	7530	17.7%
d	7259	17.1%
a	4590	10.8%
e	3849	9.1%
n	3363	7.9%
t	2295	5.4%
H	1386	3.3%
y	1386	3.3%
b	1386	3.3%
i	1386	3.3%
Other values (7)	8065	19.0%

EEA_Packaged_Policy_Indicator
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

False	2641
True	2323

Common Values
Chart

Value	Count	Frequency (%)
False	2641	53.2%
True	2323	46.8%

EEA_Full_Coverage_Indicator
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

True	3025
False	1939

Common Values
Chart

Value	Count	Frequency (%)
True	3025	60.9%
False	1939	39.1%

EEA_Prior_Bodily_Injury_Limit
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	7
Distinct (%)	0.1%
Missing	194
Missing (%)	3.9%
Memory size	38.9 KiB

20-50	1706
100-200	1590
40-100	1210
100-400	239
200-400	11
Other values (2)	14

Length

Max length	7
Median length	7
Mean length	6.283857442
Min length	5

Characters and Unicode

Total characters	29974
Distinct characters	9
Distinct categories	3 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	20-50
2nd row	20-50
3rd row	100-400
4th row	100-200
5th row	20-50

Common Values

Value	Count	Frequency (%)
20-50	1706	34.4%
100-200	1590	32.0%
40-100	1210	24.4%
100-400	239	4.8%
200-400	11	0.2%
300-300	10	0.2%
75-300	4	0.1%
(Missing)	194	3.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
20-50	1706	35.8%
100-200	1590	33.3%
40-100	1210	25.4%
100-400	239	5.0%
200-400	11	0.2%
300-300	10	0.2%
75-300	4	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	14450	48.2%
-	4770	15.9%
2	3307	11.0%
1	3039	10.1%
5	1710	5.7%
4	1460	4.9%
	1210	4.0%
3	24	0.1%
7	4	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	23994	80.0%
Dash Punctuation	4770	15.9%
Space Separator	1210	4.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	14450	60.2%
2	3307	13.8%
1	3039	12.7%
5	1710	7.1%
4	1460	6.1%
3	24	0.1%
7	4	< 0.1%

Dash Punctuation

Value	Count	Frequency (%)
-	4770	100.0%

Space Separator

Value	Count	Frequency (%)
	1210	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	29974	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	14450	48.2%
-	4770	15.9%
2	3307	11.0%
1	3039	10.1%
5	1710	5.7%
4	1460	4.9%
	1210	4.0%
3	24	0.1%
7	4	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	29974	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	14450	48.2%
-	4770	15.9%
2	3307	11.0%
1	3039	10.1%
5	1710	5.7%
4	1460	4.9%
	1210	4.0%
3	24	0.1%
7	4	< 0.1%

EEA_PolicyYear
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

2006	4964

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	19856
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2006
2nd row	2006
3rd row	2006
4th row	2006
5th row	2006

Common Values

Value	Count	Frequency (%)
2006	4964	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2006	4964	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	9928	50.0%
2	4964	25.0%
6	4964	25.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	19856	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	9928	50.0%
2	4964	25.0%
6	4964	25.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	19856	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	9928	50.0%
2	4964	25.0%
6	4964	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	19856	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	9928	50.0%
2	4964	25.0%
6	4964	25.0%

SYS_Renewed
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

True	4411
False	553

Common Values
Chart

Value	Count	Frequency (%)
True	4411	88.9%
False	553	11.1%

SYS_New_Business
Boolean

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	5.0 KiB

False	4499
True	465

Common Values
Chart

Value	Count	Frequency (%)
False	4499	90.6%
True	465	9.4%

Annual_Premium
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1166
Distinct (%)	23.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	336.5198791

Minimum	0.6
Maximum	2336.24
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	0.6
5-th percentile	107.12
Q1	160.06
median	328.6
Q3	444.14
95-th percentile	665.68
Maximum	2336.24
Range	2335.64
Interquartile range (IQR)	284.08

Descriptive statistics

Standard deviation	211.4930709
Coefficient of variation (CV)	0.6284712553
Kurtosis	9.731675721
Mean	336.5198791
Median Absolute Deviation (MAD)	147.34
Skewness	1.991912845
Sum	1670484.68
Variance	44729.31903
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
120.84	39	0.8%
127.2	34	0.7%
124.02	34	0.7%
125.08	33	0.7%
130.38	31	0.6%
133.56	31	0.6%
129.32	29	0.6%
138.86	27	0.5%
137.8	27	0.5%
139.92	26	0.5%
Other values (1156)	4653	93.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0.6	1	< 0.1%
0.64	1	< 0.1%
0.88	1	< 0.1%
1.24	1	< 0.1%
2.11	1	< 0.1%
3.71	1	< 0.1%
7.71	1	< 0.1%
10.56	1	< 0.1%
11.43	1	< 0.1%
11.6	1	< 0.1%

Value	Count	Frequency (%)
2336.24	1	< 0.1%
2227.06	1	< 0.1%
2179.36	1	< 0.1%
2034.14	1	< 0.1%
2018.24	1	< 0.1%
1880.44	1	< 0.1%
1780.8	1	< 0.1%
1679.04	1	< 0.1%
1671.62	1	< 0.1%
1630.96	1	< 0.1%

Claim_Count
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	38.9 KiB

0	4715
1	235
2	14

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	4964
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	4715	95.0%
1	235	4.7%
2	14	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	4715	95.0%
1	235	4.7%
2	14	0.3%

Most occurring characters

Value	Count	Frequency (%)
0	4715	95.0%
1	235	4.7%
2	14	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	4964	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	4715	95.0%
1	235	4.7%
2	14	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	4964	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	4715	95.0%
1	235	4.7%
2	14	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4964	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4715	95.0%
1	235	4.7%
2	14	0.3%

Loss_Amount
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	230
Distinct (%)	4.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	280.8615431

Minimum	0
Maximum	297025
Zeros	4715
Zeros (%)	95.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	23.1625
Maximum	297025
Range	297025
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	4760.610938
Coefficient of variation (CV)	16.95002771
Kurtosis	3069.375612
Mean	280.8615431
Median Absolute Deviation (MAD)	0
Skewness	51.00506603
Sum	1394196.7
Variance	22663416.5
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	4715	95.0%
54.5	15	0.3%
49.05	4	0.1%
38.15	3	0.1%
1090	2	< 0.1%
2585.91	1	< 0.1%
1911.81	1	< 0.1%
436.66	1	< 0.1%
3073.8	1	< 0.1%
5195.81	1	< 0.1%
Other values (220)	220	4.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4715	95.0%
27.25	1	< 0.1%
38.15	3	0.1%
49.05	4	0.1%
54.5	15	0.3%
76.98	1	< 0.1%
103.55	1	< 0.1%
106.28	1	< 0.1%
196.76	1	< 0.1%
217.67	1	< 0.1%

Value	Count	Frequency (%)
297025	1	< 0.1%
68571.73	1	< 0.1%
68110.03	1	< 0.1%
57491.51	1	< 0.1%
54500	1	< 0.1%
44814.41	1	< 0.1%
29497.57	1	< 0.1%
27250	1	< 0.1%
23630.11	1	< 0.1%
22054.48	1	< 0.1%

Frequency
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	31
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1582585533

Minimum	0
Maximum	121.9512195
Zeros	4715
Zeros (%)	95.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0.85
Maximum	121.9512195
Range	121.9512195
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	2.123630073
Coefficient of variation (CV)	13.41873806
Kurtosis	2455.894534
Mean	0.1582585533
Median Absolute Deviation (MAD)	0
Skewness	46.5164757
Sum	785.5954585
Variance	4.509804686
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=31)

Value	Count	Frequency (%)
0	4715	95.0%
2	198	4.0%
4	12	0.2%
1	11	0.2%
4.135649297	2	< 0.1%
2.596053998	1	< 0.1%
6.963788301	1	< 0.1%
2.257846015	1	< 0.1%
2.767017156	1	< 0.1%
72.46376812	1	< 0.1%
Other values (21)	21	0.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4715	95.0%
1	11	0.2%
1.076658053	1	< 0.1%
1.185114956	1	< 0.1%
1.289823294	1	< 0.1%
1.721763085	1	< 0.1%
2	198	4.0%
2.257846015	1	< 0.1%
2.596053998	1	< 0.1%
2.710761724	1	< 0.1%

Value	Count	Frequency (%)
121.9512195	1	< 0.1%
72.46376812	1	< 0.1%
26.31578947	1	< 0.1%
14.14427157	1	< 0.1%
10.06036217	1	< 0.1%
8.298755187	1	< 0.1%
6.963788301	1	< 0.1%
6.944444444	1	< 0.1%
5.485463522	1	< 0.1%
4.160599126	1	< 0.1%

Severity
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	230
Distinct (%)	4.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	272.4956577

Minimum	0
Maximum	297025
Zeros	4715
Zeros (%)	95.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	23.1625
Maximum	297025
Range	297025
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	4737.823352
Coefficient of variation (CV)	17.38678477
Kurtosis	3128.941195
Mean	272.4956577
Median Absolute Deviation (MAD)	0
Skewness	51.69328358
Sum	1352668.445
Variance	22446970.12
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	4715	95.0%
54.5	15	0.3%
49.05	4	0.1%
38.15	3	0.1%
1090	2	< 0.1%
5551.84	1	< 0.1%
436.66	1	< 0.1%
3073.8	1	< 0.1%
5195.81	1	< 0.1%
27.25	1	< 0.1%
Other values (220)	220	4.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4715	95.0%
27.25	1	< 0.1%
38.15	3	0.1%
49.05	4	0.1%
51.775	1	< 0.1%
53.14	1	< 0.1%
54.5	15	0.3%
76.98	1	< 0.1%
159.46	1	< 0.1%
196.76	1	< 0.1%

Value	Count	Frequency (%)
297025	1	< 0.1%
68571.73	1	< 0.1%
68110.03	1	< 0.1%
57491.51	1	< 0.1%
54500	1	< 0.1%
44814.41	1	< 0.1%
27250	1	< 0.1%
23630.11	1	< 0.1%
22054.48	1	< 0.1%
15245.03	1	< 0.1%

Loss_Ratio
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	231
Distinct (%)	4.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.151815068

Minimum	0
Maximum	1121.88
Zeros	4715
Zeros (%)	95.0%
Negative	0
Negative (%)	0.0%
Memory size	38.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0.0595
Maximum	1121.88
Range	1121.88
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	24.36932954
Coefficient of variation (CV)	21.1573283
Kurtosis	1806.688373
Mean	1.151815068
Median Absolute Deviation (MAD)	0
Skewness	40.7590306
Sum	5717.61
Variance	593.8642223
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	4715	95.0%
0.16	5	0.1%
0.13	3	0.1%
0.83	3	0.1%
2.8	2	< 0.1%
2.58	2	< 0.1%
5.04	2	< 0.1%
0.08	2	< 0.1%
5.39	2	< 0.1%
3.18	2	< 0.1%
Other values (221)	226	4.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4715	95.0%
0.07	2	< 0.1%
0.08	2	< 0.1%
0.09	1	< 0.1%
0.12	1	< 0.1%
0.13	3	0.1%
0.14	1	< 0.1%
0.15	1	< 0.1%
0.16	5	0.1%
0.19	1	< 0.1%

Value	Count	Frequency (%)
1121.88	1	< 0.1%
1112.87	1	< 0.1%
475.69	1	< 0.1%
262.35	1	< 0.1%
212.76	1	< 0.1%
148.87	1	< 0.1%
136.26	1	< 0.1%
115.52	1	< 0.1%
113.5	1	< 0.1%
78.9	1	< 0.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	PolicyNo	Policy_Company	Policy_Installment_Term	Policy_Billing_Code	Policy_Method_Of_Payment	Policy_Reinstatement_Fee_Indicator	Policy_Zip_Code_Garaging_Location	Vehicle_Territory	Vehicle_Make_Year	Vehicle_Make_Description	Vehicle_Performance	Vehicle_New_Cost_Amount	Vehicle_Symbol	Vehicle_Number_Of_Drivers_Assigned	Vehicle_Usage	Vehicle_Miles_To_Work	Vehicle_Days_Per_Week_Driven	Vehicle_Annual_Miles	Vehicle_Anti_Theft_Device	Vehicle_Passive_Restraint	Vehicle_Age_In_Years	Vehicle_Med_Pay_Limit	Vehicle_Bodily_Injury_Limit	Vehicle_Physical_Damage_Limit	Vehicle_Comprehensive_Coverage_Indicator	Vehicle_Comprehensive_Coverage_Limit	Vehicle_Collision_Coverage_Indicator	Vehicle_Collision_Coverage_Deductible	Driver_Total	Driver_Total_Male	Driver_Total_Female	Driver_Total_Married	Driver_Total_Related_To_Insured_Self	Driver_Total_Related_To_Insured_Spouse	Driver_Total_Licensed_In_State	Driver_Minimum_Age	Driver_Maximum_Age	Driver_Total_Low_Middle_Adult_Ages_30_39	Driver_Total_Middle_Adult_Ages_40_49	Driver_Total_Adult_Ages_50_64	Vehicle_Youthful_Driver_Indicator	Vehicle_Youthful_Driver_Training_Code	Vehicle_Youthful_Good_Student_Code	Vehicle_Safe_Driver_Discount_Indicator	EEA_Liability_Coverage_Only_Indicator	EEA_Multi_Auto_Policies_Indicator	EEA_Policy_Zip_Code_3	EEA_Policy_Tenure	EEA_Agency_Type	EEA_Packaged_Policy_Indicator	EEA_Full_Coverage_Indicator	EEA_Prior_Bodily_Injury_Limit	EEA_PolicyYear	SYS_Renewed	SYS_New_Business	Annual_Premium	Claim_Count	Loss_Amount	Frequency	Severity	Loss_Ratio
0	164562033	Standard	6	Direct Billed to Insured	Pre-paid	N	42602	31	1990	DODG CARAVAN SE	Standard	-1	3	1	Pleasure	-1	5	Unknown	Not Applicable	N	9	1000	25-50	25000	N	-1	N	-1	1	0	1	1	0	1	1	61	61	0	0	1	N	Not Applicable	Not Eligible for Good Student Credit	Y	Y	Y	426	16.1	Hybrid	N	N	20-50	2006	Y	N	111.30	0	0.00	0.0	0.00	0.00
1	165119133	Standard	6	Direct Billed to Insured	Pre-paid	N	42857	35	2001	BUIK REG LS-LSE	Standard	-1	10	1	Pleasure	-1	5	Unknown	Not Applicable	Y	6	1000	25-50	25000	N	-1	Y	250	1	0	1	1	0	1	1	55	55	0	0	1	N	Not Applicable	Not Eligible for Good Student Credit	N	N	Y	428	16.5	Standard	Y	Y	20-50	2006	Y	N	408.10	0	0.00	0.0	0.00	0.00
2	165166239	Standard	6	Direct Billed to Insured	Pre-paid	N	42980	30	1977	FORD TRUCK	Standard	-1	5	99	Farm	-1	5	Unknown	Not Applicable	N	9	1000	250-500	100000	N	-1	N	-1	1	1	0	1	0	0	1	47	47	0	1	0	N	Not Applicable	Not Eligible for Good Student Credit	Y	Y	Y	429	23.0	Non-standard	N	N	100-400	2006	Y	N	125.08	0	0.00	0.0	0.00	0.00
3	165198832	Standard	6	Direct Billed to Insured	Installment	N	43050	35	2002	TYTA TUNDRA SR5	Standard	-1	15	99	Pleasure	-1	5	Unknown	Not Applicable	Y	5	1000	100-300	50000	N	-1	Y	250	1	1	0	1	1	0	1	37	37	1	0	0	N	Not Applicable	Not Eligible for Good Student Credit	Y	N	Y	430	16.0	Hybrid	Y	Y	100-200	2006	Y	N	554.38	0	0.00	0.0	0.00	0.00
4	165319534	Standard	6	Direct Billed to Insured	Pre-paid	N	42496	35	1992	CHEV CAMARO RS	Sports	-1	16	1	Pleasure	-1	5	Unknown	Not Applicable	N	9	2000	25-50	25000	N	-1	N	-1	2	1	1	2	1	1	2	48	53	0	1	1	N	Not Applicable	Not Eligible for Good Student Credit	Y	Y	Y	424	16.5	Non-standard	N	N	20-50	2006	Y	N	129.32	0	0.00	0.0	0.00	0.00
5	165355034	Standard	6	Direct Billed to Insured	Installment	N	42361	30	1992	FORD RANGER	Standard	-1	5	99	Work	15	5	Unknown	Not Applicable	N	9	1000	25-50	25000	N	-1	Y	500	1	1	0	1	1	0	1	39	39	1	0	0	N	Not Applicable	Not Eligible for Good Student Credit	Y	N	Y	423	16.5	Hybrid	Y	Y	20-50	2006	Y	N	279.84	0	0.00	0.0	0.00	0.00
6	165386232	Standard	6	Direct Billed to Insured	Pre-paid	N	42357	37	1955	CHEV BELAIR 2DR	Standard	-1	3	1	Pleasure	-1	5	Unknown	Not Applicable	N	9	1000	50-100	50000	N	-1	N	-1	1	1	0	1	1	0	1	55	55	0	0	1	N	Not Applicable	Not Eligible for Good Student Credit	Y	Y	Y	423	16.0	Hybrid	N	N	40-100	2006	N	N	142.04	0	0.00	0.0	0.00	0.00
7	165708632	Preferred	6	Direct Billed to Insured	Pre-paid	N	42916	35	1972	CHEV C-10 P-U	Standard	-1	4	1	Work	1	5	Unknown	Not Applicable	N	9	1000	25-50	25000	N	-1	Y	500	1	1	0	1	1	0	1	50	50	0	0	1	N	Not Applicable	Not Eligible for Good Student Credit	Y	N	Y	429	16.0	Standard	N	Y	20-50	2006	Y	N	248.04	0	0.00	0.0	0.00	0.00
8	165951132	Standard	6	Direct Billed to Insured	Pre-paid	N	43155	31	1989	CHEV PICKUP1500	Standard	-1	11	1	Work	22	5	Unknown	Not Applicable	N	9	5000	25-50	25000	N	-1	N	-1	2	1	1	2	1	1	2	53	56	0	0	2	N	Not Applicable	Not Eligible for Good Student Credit	Y	N	Y	431	16.0	Non-standard	Y	N	20-50	2006	Y	N	210.94	0	0.00	0.0	0.00	0.00
9	165971032	Standard	6	Direct Billed to Insured	Installment	N	43046	35	2003	HOND ACCORD LX	Standard	-1	11	1	Work	14	5	Unknown	Passive Disabling-Vehicle Recovery	Y	4	1000	100-300	100000	N	-1	Y	500	1	0	1	1	1	0	1	36	36	1	0	0	N	Not Applicable	Not Eligible for Good Student Credit	Y	N	Y	430	16.0	Standard	N	Y	100-200	2006	Y	N	432.48	1	2770.88	2.0	2770.88	6.41

Last rows

	PolicyNo	Policy_Company	Policy_Installment_Term	Policy_Billing_Code	Policy_Method_Of_Payment	Policy_Reinstatement_Fee_Indicator	Policy_Zip_Code_Garaging_Location	Vehicle_Territory	Vehicle_Make_Year	Vehicle_Make_Description	Vehicle_Performance	Vehicle_New_Cost_Amount	Vehicle_Symbol	Vehicle_Number_Of_Drivers_Assigned	Vehicle_Usage	Vehicle_Miles_To_Work	Vehicle_Days_Per_Week_Driven	Vehicle_Annual_Miles	Vehicle_Anti_Theft_Device	Vehicle_Passive_Restraint	Vehicle_Age_In_Years	Vehicle_Med_Pay_Limit	Vehicle_Bodily_Injury_Limit	Vehicle_Physical_Damage_Limit	Vehicle_Comprehensive_Coverage_Indicator	Vehicle_Comprehensive_Coverage_Limit	Vehicle_Collision_Coverage_Indicator	Vehicle_Collision_Coverage_Deductible	Driver_Total	Driver_Total_Male	Driver_Total_Female	Driver_Total_Single	Driver_Total_Married	Driver_Total_Related_To_Insured_Self	Driver_Total_Related_To_Insured_Spouse	Driver_Total_Related_To_Insured_Child	Driver_Total_Licensed_In_State	Driver_Minimum_Age	Driver_Maximum_Age	Driver_Total_College_Ages_20_23	Driver_Total_Young_Adult_Ages_24_29	Driver_Total_Low_Middle_Adult_Ages_30_39	Driver_Total_Middle_Adult_Ages_40_49	Driver_Total_Adult_Ages_50_64	Driver_Total_Senior_Ages_65_69	Vehicle_Youthful_Driver_Indicator	Vehicle_Youthful_Driver_Training_Code	Vehicle_Youthful_Good_Student_Code	Vehicle_Driver_Points	Vehicle_Safe_Driver_Discount_Indicator	EEA_Liability_Coverage_Only_Indicator	EEA_Multi_Auto_Policies_Indicator	EEA_Policy_Zip_Code_3	EEA_Policy_Tenure	EEA_Agency_Type	EEA_Packaged_Policy_Indicator	EEA_Full_Coverage_Indicator	EEA_Prior_Bodily_Injury_Limit	EEA_PolicyYear	SYS_Renewed	SYS_New_Business	Annual_Premium
4954	381020700	Standard	6	Direct Billed to Insured	Pre-paid	N	43169	30	2001	VLKS JETTA GLS	Standard	-1	16	1	Work	12	5	Unknown	Passive Disabling-Vehicle Recovery	Y	7	1000	250-500	250000	N	-1	Y	500	1	0	1	0	0	1	0	0	1	35	35	0	0	1	0	0	0	N	Not Applicable	Not Eligible for Good Student Credit	0	N	N	Y	431	0.0	Standard	Y	Y	100-400	2006	Y	Y	493.96
4955	381039600	Standard	6	Direct Billed to Insured	Pre-paid	N	43065	27	1982	DODG D50	Standard	-1	8	1	Pleasure	-1	5	Unknown	Not Applicable	N	9	10000	250-500	100000	N	-1	N	-1	1	0	1	0	1	1	0	0	1	45	45	0	0	0	1	0	0	N	Not Applicable	Not Eligible for Good Student Credit	0	Y	Y	Y	430	0.0	Hybrid	N	N	100-400	2006	Y	Y	192.92
4956	381040600	Preferred	6	Direct Billed to Insured	Installment	N	42846	35	1999	LINC NAVIGATOR	Standard	-1	16	1	Pleasure	-1	5	Unknown	Passive Disabling-Vehicle Recovery	Y	9	5000	NaN	-1	Y	75000	Y	500	1	1	0	0	0	1	0	0	1	68	68	0	0	0	0	0	1	N	Not Applicable	Not Eligible for Good Student Credit	3	N	N	Y	428	0.0	Preferred	Y	Y	NaN	2006	N	Y	512.61
4957	381052900	Standard	6	Direct Billed to Insured	Pre-paid	N	42385	35	1997	TYTA CAMRY	Standard	-1	11	99	Work	10	5	Unknown	Not Applicable	Y	9	10000	50-100	35000	N	-1	N	-1	1	1	0	0	1	1	0	0	1	45	45	0	0	0	1	0	0	N	Not Applicable	Not Eligible for Good Student Credit	0	Y	Y	Y	423	0.0	Preferred	N	N	40-100	2006	N	Y	84.86
4958	381080800	Standard	6	Direct Billed to Insured	Installment	N	42471	32	1999	MERC SABLELS-PR	Standard	-1	10	2	Pleasure	-1	5	Unknown	Not Applicable	Y	9	2000	25-50	25000	N	-1	Y	500	2	1	1	1	0	1	0	1	2	20	58	1	0	0	0	1	0	Y	Without Driver Training	Not Eligible for Good Student Credit	0	N	N	N	424	0.0	Preferred	N	Y	20-50	2006	N	Y	189.94
4959	381137600	Standard	6	Direct Billed to Insured	Installment	N	42643	36	2001	PONT GR PRIX SE	Standard	-1	11	1	Pleasure	-1	5	Unknown	Passive Disabling-Vehicle Recovery	Y	7	-1	25-50	25000	N	-1	N	-1	1	0	1	0	1	0	1	0	1	66	66	0	0	0	0	0	1	N	Not Applicable	Not Eligible for Good Student Credit	0	N	Y	Y	426	0.0	Non-standard	N	N	20-50	2006	Y	Y	140.98
4960	381140200	Standard	6	Direct Billed to Insured	Installment	N	43066	27	2007	FORD F-250 SUPE	Standard	-1	17	1	Pleasure	-1	5	Unknown	Passive Disabling-Vehicle Recovery	Y	1	1000	25-50	25000	N	-1	Y	500	1	0	1	1	0	1	0	0	1	24	24	0	1	0	0	0	0	Y	With or Without Driver Training	Not Eligible for Good Student Credit	0	Y	N	Y	430	6.0	Hybrid	Y	Y	20-50	2006	Y	Y	594.66
4961	381148600	Standard	6	Direct Billed to Insured	Installment	N	42694	36	1998	JEEP CHEROKEE	Standard	-1	11	1	Pleasure	-1	5	Unknown	Not Applicable	Y	9	-1	50-100	35000	N	-1	Y	500	1	0	1	1	0	1	0	0	1	46	46	0	0	0	1	0	0	N	Not Applicable	Not Eligible for Good Student Credit	1	N	N	Y	426	0.0	Non-standard	Y	Y	40-100	2006	Y	Y	197.22
4962	381184700	Standard	6	Direct Billed to Insured	Pre-paid	N	42498	35	1999	HOND CR-V EX	Standard	-1	11	99	Pleasure	-1	5	Unknown	Not Applicable	Y	9	-1	NaN	-1	Y	300000	Y	500	2	1	1	0	2	1	1	0	2	49	49	0	0	0	2	0	0	N	Not Applicable	Not Eligible for Good Student Credit	0	N	N	Y	424	0.0	Hybrid	Y	Y	NaN	2006	N	Y	358.24
4963	381258900	Standard	6	Direct Billed to Insured	Pre-paid	N	42891	35	1999	FORD F250 SPDTY	Standard	-1	17	99	Pleasure	-1	5	Unknown	Not Applicable	Y	9	1000	NaN	-1	Y	100000	Y	500	1	1	0	1	0	1	0	0	1	35	35	0	0	1	0	0	0	N	Not Applicable	Not Eligible for Good Student Credit	0	Y	N	Y	428	0.0	Preferred	Y	Y	NaN	2006	Y	Y	484.42

Overview

Variables

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Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Common

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length